I think as everybody is well aware, insurance claims operations are facing significant pressures to transform and achieve operational efficiencies. For many years, challenges have been faced in terms of delivering change, more efficient processes, as well as improving the customer experience at the point of claim, with many claimants now expecting instant updates, faster payments, and a seamless digital interaction. In conjunction with that, claims complexity is an area which increasingly drives change as well as customer frustrations, and many of those can be dovetailed with the insurer experience, where we see greater fraud, as well as complexity in the adjudication and management of claims.

In today’s podcast, we’re going to explore how insurers really need to adapt to the latest SaaS and AI initiatives to drive the future claims operations, providing that better customer experience. And in addition, we need to look at how the operational experience is very much tailored around the propositional challenges that insurers face.

To explore these, I’ve got Tarik Dadi, founder and CEO of Qantev. Qantev is an AI-powered platform helping health insurers and life insurers transform their claims operations through data extraction, automation, and advanced analytics. And I’m very pleased to say, Tarik has got a smile on his face. Not that anybody can see, looking very pleased to be here with me. Before founding Qantev, Tarik led the data science and innovation initiatives within several major financial institutions, including AXA and Natixis, where he focussed on applying advanced analytics to insurance and financial services use cases.

So, Tarik, thanks for joining us today and glad to have you with us!

Tarik Dadi: Thanks, Rob. Happy to be here.

Rob McLean: Awesome. Okay, so to begin with, I think a good starting point would be very much looking at what challenges did you see in the industry that really drove the need to change and to come up with the idea of Qantev?

Tarik Dadi: Yeah. So, it’s quite intertwined with my professional journey in some ways. So, I started my career at AXA Group, which led me to work with many AXA entities across the world. And one thing that struck me while deep diving in the different claims operations at the time, especially in the health and life business line, is how manual the processes are and how most of the complex decisions that need to be taken, are taken solely based on the know-how of the armies of nurses [and] doctors that are spending their day reading documents and making tonnes of checks based on their know-how. And this while, we are seeing a tremendous increase of the volume of medical claims and this rampant medical services inflation of 10% a year all across the globe. And all of those observations made it clear for me that things needed to change, so that insurers can scale their operations, if they want to get a bigger portion of the pie, if we say it this way. And while they deliver, they need to still deliver a better quality of service, which is mostly driven by how fast they can adjudicate the claims they receive, and also be able to go beyond being a simple payer, being a partner. And for that, you need resources instead of focussing your resources on, let’s say, tasks that can be a bit of a low value for when you look at them, nowadays. It’s allowing them to focus on more advanced services for the members, especially when it comes to health, where a lot of members are expecting not just the payer, but somebody that can help them through their patient journey.

Rob McLean: Excellent. So, I think certainly from our experience, we see very similar aspects where claim administration has become a commodity. The knowledge that resides within claim assessors’ heads is very constricted and can create delays, backlogs, as well as increasing the demand on those resources and of course, the cost that goes with them to the insurers. So definitely automating and streamlining that has not only a positive output for the insurer, but also a better experience for the claimants who are interacting with them.

If we look from the insurer’s perspective, claims management can often be seen as an expensive overhead. As part of that, where do you see Qantev really enabling the improvement of the processes and the decision making within the organisations?

Tarik Dadi: Yeah, so I see it in two ways. It’s first, increasing the output of those claims operations, enabling them to handle a much higher volume of claims, faster. And secondly, automation. And it’s for me; it’s always a two-step aspect. But automation is very hard when it comes to dealing with coverage, in our case, coverage of human health. And for me, all of this, when it comes to increasing the outputs, putting in place automation, it starts with the data.

You can have all the fancy AI models or operation workflow, orchestration, tooling. If the data flowing is bad, the waterfall of decisions that come afterward is going to break. So that’s why we need to start with automating, first of all, data entry. Still, a lot of insurers on the market need to deal with a huge inflow of unstructured data, of documents coming from providers or members. That needs to be kind of put into the system. This and a lot have experimented with OCR and everything, but the granularity of the information that is put into the system, or by human-driven data entry operations or by OCR-driven operations is still not granular enough, and not at the level of quality that is required to be able to do any kind of intelligence and automation afterward.

Then when you solve that step using modern approach, we need to tackle the other topic, which is all the tech checks that need to be performed from contract intelligence. So, understanding the coverage, medical intelligence, understanding the different medical aspects of the claim and finally the fraud and abuse intelligence so that you are able to do any kind of automation at some point.

Rob McLean: Interesting. I think you raised a good point there, which is from our experience, again, we see a lot of insurers looking at the real use cases and value AI can bring to their organisation. We all acknowledge the movement in the industry toward more AI-driven capabilities, but identifying those key areas where AI can have real value is sometimes challenging. And it certainly sounds as though you’ve pulled out a real use case here, and that’s at the foundation of Qantev’s proposition.

Tarik Dadi: To be honest, today the AI adoption rate is still quite low, when it comes to claims operations, especially on the health side. It’s a buzzy word that the industry has overused and that every software vendor has sprinkled over their products to the point where there is a bit of disillusionment today, if we can say so. And nowadays, you know, with all the agentic craze, there is also a bit of… the insurers are a bit worried when it comes to that. I think they evolved a lot, and now they expect ROI from those initiatives and they expect also a mix of both AI expertise and domain expertise. They don’t want any more to this kind of off-the-shelf solutions that are targeting the Agri industry, the car industry, and at the same time the insurance industry. They want people that understand their business and that can apply and that can bring solution, AI-driven solutions to that. So as shared in the previous question, really it starts with solving the data question. And that on its own is hard. It’s hard being able to extract the right information to infer what is the right CPT code to apply to a line item, what is the right ICD code to apply to the diagnosis? Bringing the right tooling to that operation is already a challenge. But what gets us excited at Qantev is trying to reproduce through AI all those checks that are currently done by the claims operators that are often nurses or doctors that are working in the back office. When deciding what to do with a claim, they need first to be able to check if the claim is covered by the policy, they need to check if the care that has been billed is necessary from a medical standpoint. They need to check if the medical services are coherent with the diagnostic. If the price of the service is coherent with what is observed on that specific market. So many, many checks that live in their heads that are based on their cognition, that need to be reproduced through AI. And all of those checks require some specialised approach to understand what is the grounding data that enables them to make a decision. And at the end of that, you have to add to all the capacities in regard to fraud and abuse. When it comes to identifying the anomaly and then explaining it to making it, to make it actionable for the SIU teams to be able to recover or stop any kind of dynamic that is going there.

So, all of this requires tonnes of AI techniques to be stacked together and to be embedded into a software that is capable, that understands how those operations work and be a part of their transformation.

Rob McLean: I think it’s a good point that you’ve raised there. When we look at the completeness of proposition, certainly from a lot of the capabilities that may be able to be sourced in the market, many of them don’t provide that full end-to-end capability of the data entry, through the administration, the adjudication, but most importantly, also flagging and identifying the fraud elements or where human intervention potentially needs to come into play to really call that out. And the retrospective looking at the performance through the lifecycle of the claim management process. So, it certainly sounds from a Qantev perspective, as though you’ve brought that all together in that one cohesive offering. If I were to pull a crystal ball out there and, you know, certainly fortune telling is a unique art in our industry. Where do you see the future, if we were to look five years ahead from now, from a claims operating model and a technology and legacy standpoint?

Tarik Dadi: I believe that’s a great question. I believe claims are going to see some heavy changes in the years to come. Status quo is not an option anymore. You cannot just throw money at the problem. Now insurers understand where the impact can be. They have experimented enough and they are looking for technology that can blend, as I said, AI expertise with domain expertise. So, I see a bigger chunk of the volume of claims being automated, especially the ones that we believed were too complex, that were too sensitive. We are going to we are going to see a huge jump in terms of trust in AI models when it comes to tackling those specific, those specific claims that we believed are difficult to handle through an automation setup.

But I see also a more augmented style of claims management. The software is not only about automating, it’s about augmenting the capacity of some specialised operators that are working in claims operations. So it’s about bringing them this kind of 360 view of the claim, allowing them to study complex patient journeys, highly sensitive ones, VIP and kinds of claims in a more thorough way, in an enhanced way so that to again come back to that throughput level, you have this very specialised operators, very knowledgeable, experts that just need to be enhanced in their ability to handle more claims per day than they are doing today because of a lack of tooling.

Rob McLean: Excellent. So, it sounds like a very much a strategy aligned to insurer’s  agentic frameworks, whilst recognising that need for human interaction and then supporting the human interaction element of the processes which we all acknowledge will still be there in the future. I think I am slowly running out of time, but maybe we have time for one last question. For any of the insurers out there that are beginning their AI journey specifically around their health claims operations, what would you see or recommend as the first step they could take and what their strategy should really look like?

Tarik Dadi: So, one of the mistakes that we see often is that insurers acquire a new tool, an AI-driven tool, before thinking how it’s going to transform their operation. So, it’s for me, always the first step is having a clear transformation plan of what they want their claims operation to look like after implementing new tooling and bringing some AI capacity capabilities. And of course, whatever that transformation plan is going to be, the first, first step is to make sure to start with the data, making sure that the data that you are getting, is that you are starting with, to enable that workflow is the right level from the get-go. If not, it’s going to just create issues afterward.

Rob McLean: Excellent. Tarik, thank you ever so much for sharing all your insights today. I think your perspective on transforming the claims process, our risk exposure, and innovating in the claims space is very insightful for certainly us and hopefully also, to the listeners that are out there. You clearly show that you’re at the forefront of the technology and technical shift in the industry in this area, and certainly from a Sapiens perspective, we’re very proud to be partnering as an ecosystem partner with Qantev.

To all our listeners out there, thank you ever so much for joining us as we’ve deep-dived into the future perspective of insurance claims. And if any aspects of today’s conversation really resonated with you, we’d love to hear your thoughts. Please feel free to connect with us on social media. Share your feedback on this podcast, even if you don’t necessarily disagree or agree with some of the points. And subscribe to the podcast so you can hear any of the new and exciting episodes that are still to come. Until next time, this is Sapiens Insurance 360 and thank you for listening.

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The post From Legacy to Learning Systems: AI’s Transformation of Health Insurance Claims appeared first on Sapiens.

The countdown to 2026 has begun in earnest, and for insurers across the industry, 2025 was a year that saw AI transition from experimental pilot programs to production-ready decisioning systems, from underwriting to claims processing and fraud detection, AI and AI decisioning. We’ve moved past the buzzword phase into everyday usage, yet significant questions still remain — how do we ensure AI decisions are explainable and compliant? How do we balance automation with human oversight, and how do we build trust in systems that are reshaping the very foundation of insurance decisioning? With regulatory scrutiny intensifying, data quality challenges persisting, and competitive pressure mounting, 2026 may be the year that separates the leaders from laggards in AI decisioning adoption.

With us today to help us look back at 2025, and the road ahead in 2026 for AI decisioning is our special return guest, Sapiens’ own Rafael Goldberg. Rafi heads up Sapiens Decision and brings 20 years of experience in product strategy and delivery. Rafi, welcome back to the show. It’s been a while, but you’re here now to walk us through the year that was. And the year that will be for AI decisioning.

Rafael Goldberg: Thanks, Mark. It’s great to be back and really hard to believe we’re at the end of the year. 2025 was definitely a milestone and we’re super excited about what’s to come.

Mark Sidlauskas: Yeah, that’s great. So let’s jump off from there. A lot of milestones were achieved in 2025. Talk to us about what’s happened in Sapiens Decision. Talk about some of the technology enhancements, the market, what’s going on?

Rafael Goldberg: Yeah. So 2025 has been very exciting for Sapiens Decision and the decisioning market generally. And that’s really as you talked about in your introduction, making AI real and combining it with what previously has always been a very declarative discipline. And so the combination of the probabilistic side of the house in AI and the deterministic side of the house in decisioning, is super powerful. And now we’re getting the best of both worlds. We’re getting customers to market quickly. We’re getting insights that previously would take a significant lift in IT to achieve. And [we’re] really seeing the promise that we’ve always had between business and IT when it comes to decisioning, just getting that much more potent. So a lot of milestones in terms of new customers, a lot of milestones in terms of new products, which we’ll talk a bit about. And also, I think just the category itself, the analysts, the major analysts have been releasing some very exciting and major reports on the category. And customers are taking note and realizing that to be competitive, they have to engage in this space.

Mark Sidlaukas: So congratulations on being named a leader in the Forrester Report on AI Decisioning platforms. That’s a huge accomplishment!

Rafael Goldberg: Thanks, Mark. It’s really the great work of the team and the customers who have helped guide us and influence the roadmap. Forrester has done a tremendous job with that report and the competition was great. I mean, that’s a vibrant market where competitors are pushing each other to leapfrog and provide more value to the market. And they really crystallized, I think, the category, they got there early [and] talked about…they’ve named the category AI decisioning. And they really, at the heart of the matter, they talk about [how] enterprises compete on decisions, the ability to make precise, rapid, and adaptable decisions. And that’s really where they focused. And we were very pleased with the Leader status.

Mark Sidlauskas: Great. So before you mentioned some of the capabilities that are being brought to market right now, let’s talk a little bit about that. So what are the new capabilities that really extend what the former decision management had been and make that an AI decision platform? What are some of the new use cases and technologies?

Rafael Goldberg: Definitely. So I think the fundamental aspect of this category is that bringing together of what previously were siloed disciplines. So disciplines in their own right, but siloed, number one. And number two, the application of AI to the decision process. And so really you can think of the three aspects of an AI decisioning platform or AI. And that can be generative AI and as well as traditional AI like machine learning. It’s decision management, which is the evolution of business rules. So you can think of those declarative decision models which are requirements and also code and then finally data and analytics. And I think that piece was really the missing piece in the platform. You can think of data analytics and analytics as previously a very specialized field. Data scientists and the business and IT groups that were creating decisions and deploying them weren’t getting that real-time feedback and the ability to monitor and adapt the outcomes. And now these platforms that are bringing these three areas together are getting a much faster and tighter loop of optimization. And so, we’re very excited about combining these disciplines and the use case, I think, really at a general level, is what I just mentioned, which is number one, using AI to get decision models to production quickly. And number two, being able to get that feedback and act on that feedback rapidly because of the combination of the analytics with the decisioning.

Mark Sidlauskas: So that’s a huge quantum leap from where decision management was previously. Now you can actually use what I would suppose are decision analytics. What’s going into that full decision? All the different sub decisions that have to take place to achieve an outcome and then optimizing on that outcome, whether it’s a set of KPIs or some other business metric, to be able to optimize what that outcome is, that what the platform delivers to customers?

Rafael Goldberg: Exactly. You really hit the nail on the head there. So not only are you getting the observation of the observability of all of that detail, all of that granular detail of what’s happening with the outcome of the decision, but you’re also now being able to optimize and with the application of AI, what we’re super focused on and excited about in 2026 is what we’re calling optimized AI, which is part of our decision AI roadmap, and that is now your AI partner. Your AI agent will be monitoring 24 over seven what’s running in production and based on the KPIs that the business is setting, it’s going to be watching for drift. It’s going to be telling you when things are happening that you may want to take a look. And it’s also aware of the details in the decision architecture, in the decision models themselves. And so it’s able to actually say, hey, I noticed you were getting less people eligible for that product. I think that if you made this change in this part of the decision model, I’ve already done it in the background. Run a production test run and you actually see this percentage increase. So just a really, a quantum leap, as you said in the opportunity for the business.

Mark Sidlauskas: So just looking forward, I think 2026 is going to be the year of the agent. Agentic AI, I think that’s really going to come into place. What you’re describing is that that scenario. So is that going to become real for our customers in 2026? What could we expect down the road?

Rafael Goldberg: Absolutely. It does feel like science fiction, but it is real. It’s here. We’re proving the concept out actively, both in hackathons and in analysis and design work. The frameworks are available and it’s really about, implementing it in a user experience, in a paradigm that makes sense. I think those are fairly well established with some of the available, consumer technology and enterprise technology. And so it’s putting it all together, and I’m very confident that companies will be able to interact with that kind of system in 2026. And it really is a game changer and it’s exciting. I think there’s a lot of questions about trust and about, accuracy, but from, from our work, we see, there’s really an opportunity to have the AI agent as a partner, not as an overlord, if you will, so that that that AI agent is,  really doing the work that we’re already doing as humans, but much, much more rapidly, and it still just is giving the business or the human the ability to review what’s been recommended. Do any testing that we want to and then and then redeploy. So it’s that whole human in the loop governance opportunity.

Mark Sidlauskas: Thanks so much for your insight today, Rafi! As we look toward 2026 and AI decision technology continues to evolve and become indispensable for insurers, it’ll be interesting to see how carriers implement these systems balancing efficiency with explainability, automation with accountability, and innovation with trust. Your perspective on how customers can navigate these challenges gives us a lot to think about as we plan for the year ahead.

To our listeners, as always, thanks for joining us. We have so much more exciting content planned for the rest of 2025 and 2026, and we’d love to hear from you. Connect with us on social media, share your feedback, and don’t forget to subscribe to the podcast, so you never miss an exciting and insightful episode. Until next time, this is Sapiens Insurance 360. Thanks for listening!

The post The Road Ahead: AI Decisioning 2026 appeared first on Sapiens.

A decade ago, digital insurance transformations focused primarily on efficiency gains, expanding distribution channels, making customer journeys better. Today, carriers face a fundamentally different reality: escalating climate volatility, increasingly sophisticated cyber threats, and the widening protection gaps. These are demanding a fundamental shift from reactive coverage models to proactive prevention strategies. In this episode of the podcast, Onno Bloemers, partner of the First Day Advisory, explores how the insurance industry can evolve beyond its traditional role as a post-loss financial safety net. We’ll also examine the emerging paradigm of insurance as an everyday safety service, one that actually helps customers identify risks and avoid losses before they occur, rather than simply compensating for them after the fact.

Onno, welcome to the show! So glad you’re here to discuss this subject!

Onno Bloemers: Well thank you, Dean. Very happy to be here. Thank you for the invitation!

Dean Richardson: Great. So let’s begin. So, Onno, why do you believe predict and prevent is the next frontier for insurance?

Onno Bloemers: Sure. Well, the traditional pay when it happens model, is simply no longer sustainable. We see climate risks. We see health costs. We see mobility shifts. All these developments are overwhelming the traditional paradigm. Now predict and prevent, reframes insurance as a safety service using data and incentive partnerships, all geared to avert loss. And this way, by preventing by adding prevention to the insurance product, we can protect both customers and balance sheets. And we see this across business lines. We see IoT move from pilot to proof. In property homes, we see electrical fires being monitored and being and with early face recognition, we see all kinds of new leak sensors, weather-driven alerts, developments on the catastrophe site where homes are being fortified. All these developments across these different insurance sectors already show results. We all understand that the best claim is the one that didn’t happen. So prevention is not something you build on. It’s in fact, a new business model.

Dean Richardson: Thanks for that, Onno. So as a follow up, so what’s driving insurers globally to embrace this shift plan?

Onno Bloemers: Well, first of all, we live in a time where sensors are now cheap and connectivity is nearly everywhere. We have AI technology to separate noise from signal. So in short, we can detect much more. And we need to use that data, that information. All these data points, weather reports, and early signals of wildfire smoke or hill risk. Let’s put them to use, let’s help our customers to react in time to respond to this. And this is across all business lines.

Now, the second reason why this shift is now taking place is because of customer expectations. People understand that a payout is one thing, but having your life or business interrupted is much more important, and this approach helps customers to avoid disruption. Prevent the fire, avoid the crash, keep a website safe, everything like that. So insurance becomes something of a valued partnership. Not anymore the grudge purchase it used to be.

Now lastly, [the] third reason why this is happening is the increasing regulatory and societal pressure. We see the widening protection gaps in climate-exposed geographies and regulators and policymakers are all looking at ways to increase resilience and doing that in public-private collaborations where there’s an important role for insurers. Now prevention becomes the insurers’ social license to operate.

Dean Richardson: Okay, Onno. So it seems fairly obvious [that] it’s good for the customer, it’s great for the insurer. The claim either doesn’t happen or the claim is mitigated. So all sides win. So what makes predict and prevent hard for insurers to implement?

Onno Bloemers: Well, unlike many other innovations or transformations we’ve seen over the past years, this is one that affects every part of the insurance value chain. I think that’s a tough cookie to crack. It impacts your underwriting. It impacts your claims, your pricing, your distribution. So and it all has to work together in this new reality, and that’s kind of an operation that requires cross-functional ownership and incentives and KPIs. That’s an important element here. The second barrier may be that there are many data points, many pilots, or many projects where we have the insights, we have the data, but we don’t yet use them to trigger workflows. And there lies a job to be done. Translate available data into concrete customer value propositions and actions. So the leak alerts lead to a signal, which leads to a contractor that can dispatch to fix the problem before the claim becomes a really large claim.

Now the last point, third point here. That’s a matter of adoption and trust. Customers need to understand the value of devices, sensors that help them to keep safe. And of course, there may be matters of distrust. And you will have to convince your customers that it’s in their best interest. We’re here to help you to avoid the hassle. All this means that insurers need to organize prevention, not just as something on the side as another innovation experiment, but really as a core product.

Dean Richardson: Yeah, I think that’s a topic for another podcast there, Onno. So where the issue of trust, that consumers will trust their data in Tik-Tok, but not with their insurer. So there’s the next topic. So shifting gears slightly, so what role does technology have to play versus the behavior shift?

Onno Bloemers: I think technology is the key enabler here, by providing not just the signals and the insights, but also by making it easier for the customers. Insurance has now the potential to become something it has never been: [a] trusted partner in daily resilience. But what’s required is that it’s easy to install any new sensor or configure a specific app. It has to be very effortless, otherwise it’s never going to work. So getting the right technology here, developing it with partners is critical.

Now secondly, that technology also has to support the rewards programs where you try the safe behavior to lower premium or bundled services or cash rewards elements like that. So it is all seamlessly integrated. And lastly, the technology has to work in such a way and needs the guardrails to make it trusted to have clear boundaries on where you use the data opt-ins and all these safeguards that are required. In this way, you can make the transition from policing the risk to partnering on resilience.

Onno Bloemers: Thanks for that Onno. So we’re actually running short on time, so here’s my last question. How should insurance leaders start the journey?

Dean Richardson: I think it’s important that there is a clear and shared vision within the organization. There has to be an ambition that is shared and a roadmap. Otherwise, people will tend to keep working as they have always worked. But secondly, it’s also important to set up programs and pilots that quickly deliver results and build confidence that you’re on the right track. So pick one or two business lines, for instance, in motor insurance or in home. Find the right partners. There’s lots of examples out there of successful programs and what’s required to make that happen and use that to build the initial traction. Set up your own organization and build from there across your portfolio. And in the end, you need to bake it into your rates and your underwriting and all these aspects. But it’s important that you get some of these initial projects out there and stick to it. Don’t give up too quickly, because prevention is also a long-term gain. But it’s important that we play it.

Dean Richardson: Thanks so much for your insights today, Onno. So, you’ve shown us why prevention is no longer just a value-add feature, but is a critical path to maintaining relevance and competitive advantage in an insurance industry facing rapid disruption, and also why the insurance sector must fundamentally rethink its purpose and value proposition for the decades ahead. For 400 years, insurers’ primary purpose was that in the event of a loss, they put the insurer back in the position they had before they encountered that loss. So your car was in an accident, then they [had] to repair it. The house was flooded due to a water leak. Then they repaired or replaced the damaged items. We’re now moving to a prevent or mitigate model, which is the holy grail for insurance.

And whilst we’re not there yet across all lines of business, we are making sizable inroads into the journey.

To our listeners, as always, thank you for joining us. We have so much more exciting content planned and we’d love to hear from you. Connect with us on social media. Share your feedback, and don’t forget to subscribe to the podcast so you never miss an exciting and insightful episode. Until next time, this is Sapiens Insurance 360. Thanks for listening.

The post The Prevention Imperative: Reimagining Insurance for a More Resilient World appeared first on Sapiens.

Well, here we are in Q4 of 2025, with a little more than one month left in the calendar year. For life and annuity insurers, it was a year that saw record net income approaching roughly $51.1 billion, and faster transfer of wealth from Baby Boomers and Gen X’ers to younger generations. AI technology remained a monkey on many insurers’ backs, as they know they need to eventually adopt it.

But for now, we remain risk averse. With interest rates shifting, demographic trends, unprecedented demand, and technology shaping how we serve customers, 2026 might be a year that tests our industrious agility and vision. With us today to help navigate this uncertainty is Ken Leibow, founder and CEO of InsurTech Express. Ken has over 38 years of insurance industrial experience, with an extensive background in insurance technology, for distribution and back-office systems. Prior to founding InsurTech Express, Ken worked for Genworth Financial, Mutual of Omaha, and was vice president of operations at Diversified Underwriters Services Inc. While he was COO of Integrated Insurance Technologies, then-owned by SelectQuote, Ken built the largest life insurance data exchange hub in the industry, processing over one million policies per year and $30 billion of annuities. Ken, welcome to the show and thanks for joining us today!

Ken Leibow: My pleasure, Kevin. Happy to be here and provide some insight!

Calvin Zhai: Great. So to start, AI has been the buzzword of 2025. While some carriers have completed their digital transformation, others are just starting. But what does real technology adoption look like for carriers heading into 2026? What separates a company that [is] generally transforming from those that are just experimenting?

Ken Leibow: Yeah, that’s a great question. What I’m seeing across the industry is a big difference between digital projects and true digital transformation. I mean, carriers that are really moving forward, not just layering new tech on top of legacy systems or legacy processes, but they’re really re-engineering the workflow from the ground up. For example, the most innovative companies are embedding agentic AI into their new business and policy admin systems. I mean, these tools, they don’t just automate, they think and act dynamically, and they guide underwriters, distribution partners, and service teams through data-driven decisions. So heading into 2026, I would say the winners will be those who align technology with business outcomes, not just those who experiment with AI just because it’s trendy.

Calvin Zhai: Awesome. Interesting. Thanks for sharing your take though, Ken. So next question. After years of exceptional growth, projections suggest that 2026 would be more about normalization and sustainable performance. From your perspective, how should companies balance the need to maintain profitability while still investing in innovation and growth for the long term?

Ken Leibow: Well, sustainability really is the theme, I would say, for 2026. I mean, after several years of aggressive investments, you know, most carriers are now asking, how do we maintain margin while still innovating? And the answer, in my opinion, is strategic prioritization. Not every innovation delivers equal ROI, but the focus needs to be on technologies that create measurable, lasting impact like automated underwriting and straight-through processing. We always defined straight-through processing as submission to commission. Anyway, at the same time, partnerships are key. I mean, I’m seeing more carriers collaborate with insurtechs and distributors instead of building everything internally. So that reduces cost, speeds deployment, which means speed to market, right? And keeps innovation flowing even during tighter budget cycles. So my advice is innovate smart, not too big, focus on initiatives that strengthen both the balance sheet and the customer experience.

Calvin Zhai: Thanks, Ken. Thanks for sharing what you see in the industry. So moving on, it’s obvious that the way consumers purchase life and annuity products is rapidly evolving. How do you see the distribution landscape changing in 2026 — whether it’s the role of independent agents or advisors, direct-to-consumer channels, or hybrid models? And how should carriers be thinking about their distribution strategies?

Ken Leibow:Well, you know, I hate to use the old cliche, but, you know, most life insurance is still, sold and not bought, right? So, you need to have an advisor in the picture, who can really help consumers.But as we move toward a digital experience, what we’re seeing on the wholesale side with these distributors is they’re providing platforms to recruit agents that allow an agent to put on their website, quoting tools, e-App tools, [and] content for consumers. Then the agent can run, let’s say, a targeted marketing campaign on social media and a client goes to the website.They may run a quote, submit [an] application, put their, contact information and that generates a lead for the agent to either follow up or help the consumer. And then we see some hybrid approaches where if the agent already has a relationship with their customer, they could start the application filling out the part one, and then they could hit a button and send the link to the client to answer more of the invasive medical questions, right? And then also have a cost center, available for the whole fulfillment process. So what I’m seeing is, bottom line is, the carriers that succeed will combine high-tech and high-touch experiences seamlessly. And those that stay siloed, they risk losing market share to more digitally fluent distributors.

Calvin Zhai: Excellent take there, Ken, thanks for sharing! Now, with over 4 million Americans turning 65 each year through 2027 and trillions in wealth transferring between generations, we’re seeing this unprecedented demographic opportunity. But are carriers truly prepared to serve this market?

Ken Leibow: Well, yeah, that is the trillion-dollar question. I mean, we’re watching the largest transfer of wealth in history. I mean, from Boomers to Gen X, from Boomers and Gen X, to Millennials and Gen Z’ers right? So but many carriers still communicate as if they’re selling in the 1990s! I mean, the next generation really expect simplicity, transparency, and speed. You know, they want to have that kind of Amazon experience, buy life insurance like they would shop for everything else right on their smartphone in minutes, with clear value and digital servicing. I mean, a few carriers are adapting, offering instant issue products, mobile engagement and personalized journeys, but many are still catching up. So this is also an opportunity to diversify distribution. I mean, bringing in more young, tech-savvy agents who understand how to reach the new audience. I mean, the carriers that reimagine their brand voice and modernize engagement will capture this generational opportunity.

Calvin Zhai: I believe, you know, keeping the customer in the center of all your sales processes will be important. So we’re running a little short on time, and here’s my final question for you. Underwriting has traditionally been one of the most labor-intensive and time-consuming aspects of our new insurance. With AI and predictive analytics advancing rapidly, how do you see underwriting evolving in 2026?

Ken Leibow: Yeah, I mean, underwriting is where AI is making one of the biggest impacts. We’re shifting from a rules-based to intelligence-based underwriting instead of hundreds of static rules, AI models can now evaluate data from electronic health records, from Rx prescription data, lab results, lifestyle data, and even the part with the part two questions in their life application. And they can do all this in real time. So what’s emerging is predictive, agentic underwriting. I mean, systems that can orchestrate data sources and learn from outcomes. And what that means is that fewer manual reviews, faster decisions, and better risk selection, right? So I would say by late 2026, I expect like 70% or more of simplified issue cases to use some of this automation, you know, and some may be completely, fully automated. Even traditionally, traditional underwriters, underwritten cases, will use AI for triage and decision support. The next evolution is about trust and transparency, building models that are explainable and compliant.

Calvin Zhai: Thank you so much Ken for sharing your insights and perspective on the market. As we look toward 2026, the L&A insurance industry needs to balance the need to adapt to changing market conditions and capitalizing on this unprecedented demographic opportunity and technological capabilities. Your perspective on how carriers can navigate this landscape, from AI implementation to product innovation to distribution evolution, gave us so much to think about as we plan for the year ahead.

For those of you who want learn more about Ken’s work and stay updated on insurtech trends, you can find InsurTech Express online and follow Ken’s insights on the latest developments that are shaping insurance. And as always, thanks for joining us. We have so much exciting content planned and we’d love to hear from you. Connect with us on social media, share your feedback, and don’t forget to subscribe to the podcast so you can never miss an exciting, insightful episode. Until next time, this is Sapiens Insurance 360. Thanks for listening!

The post The Road Ahead: Life & Annuities Insurance 2026 appeared first on Sapiens.

Managing General Agents, or MGAs, have become a powerhouse in the insurance market, with direct written premiums exceeding $102 billion in 2023, growing 13% year over year, and outpacing the overall property & casualty market’s 10% growth. What was once a niche distribution channel has evolved into a powerful force reshaping how risk is underwritten, distributed, and managed. MGAs are no longer just intermediaries. They’re becoming strategic partners for reinsurers seeking agility, specialized expertise, and access to profitable niche markets. In today’s episode, “The $100 Billion Shift: Reinsurance’s Booming Relationship with MGAs,” we’ll explore why this partnership is accelerating, what’s driving reinsurers to deepen their MGA relationships, and how technology is enabling this transformation. And joining me today to discuss this fascinating topic is Mark Geoghegan, founder and host of the Voice of Insurance podcast, which is sponsored by Sapiens company AdvantageGo. Since 2019, Mark has hosted “The Voice of Insurance” podcast and brings over 25 years’ experience in insurance, reinsurance, and insurance journalism. “The Voice of Insurance” podcast attracts a broad range of industry leaders who discuss the market’s hottest topics and where it’s headed.

Mark, welcome to the program! It’s a real honor to have you on the show today!

Mark Geoghegan: Oh, it’s an honor for me, Darren. And I’m really happy to be here. I’m looking forward to our discussion!

Darren Graves: So, Mark, let’s jump in! To give us some background color, can you describe for us the MGA market and what’s driving its rapid growth?

Mark Geoghegan: Yeah, absolutely. Darren. MGA, let’s just remind ourselves, that’s a managing general agent that’s effectively a professional underwriter who’s underwriting on behalf as an agent, on behalf of somebody else. MGAs have always been with us, particularly because it’s such a great way of syndicating and trying out new risk. Without taking too much risk, for any one insurer. For example, say, maybe 100 years ago when the first, the Wright brothers were flying, there was, somebody probably started and, an aviation insurance MGA. It’s a really great way, instead of having one insurer and asking them to put all their eggs in this aviation basket and, invest all that expertise and the claims and really technical stuff, somebody said, no, I’ll do that and all. I’ll find 20 insurers to do 5% each. And that was really helpful. And obviously as the aviation class grew, they could, they might start their own aviation department when they see this thing’s really taken off, excuse the pun. And, but we’ve got a real perfect storm at the moment, particularly. We’ve had this over the last five years. We’ve had the market itself has changed, has turned. Obviously, MGA is going to operate better in excess and surplus lines in specialty markets. And we’ve had a situation where the Admitted Lines market has shared a lot of business into the excess and surplus markets in the U.S. So the growth of the excess and surplus lines market and the growth of MGA has been parallel. So that we’ve had that push that’s been pushing out, then the risk itself. We were talking about aviation 100 years ago. Well, 15 years ago, cyber, no one had ever done it. And of course, it’s a natural thing using that risk-sharing syndication mechanism. And that expertise mechanism. Cyber was, of course, it was absolutely pioneered and it still is and dominated by MGAs. But, and of course, and in the recent times we’ve had the emergence of those perils we used to call secondary perils. But, you know, no one calls them that anymore. Wildfires, flood. You’ve got really interesting specialist risks like M&A and surety. Also and even things like carbon credits. I had someone on the podcast the other day, it was fascinating. Carbon credits, who knew? But you know, that’s going to be a massive business over the next 30, 40, 50 years of become a new asset class, like a new oil. It’s amazing. So these are naturally places where MGAs and so that’s where it’s come from. So that’s the push. And then the pull is reinsurers themselves. The global major insurers have all consolidated hugely. And they consolidated the way they buy reinsurance. And it means the reinsurers don’t get some of the old vanilla business that they used to, that this is, you know, like homeowners in Idaho. They don’t get that anymore. They get asked to take on massive tail risk, like a massive earthquake. You know, for, the writing the program of AXA, Allianz, AIG, and they don’t like, they’re getting more volatility than they used to. So this, if you can find lots of niche businesses and back them, and aggregate them, you get a lot more steady, less-volatile business. So there’s the pull factor as well. So which explains why it’s been so, such a big deal.

Darren Graves: Yeah. And I think that what you say, that expertise, that underwriting knowledge is key when it comes to underwriting these risks, risks for the carriers ultimately.

Mark Geoghegan: Yeah, ultimately. And the one other thing is actually technology itself. As before 30 years ago, you might have a specialist underwriter and they had to be specialists because of, they were doing such a niche class, but you knew they were going to have a higher expense ratio just because every time you add another hand in the value chain, you add another 10% and you add another load of errors and data entries, and things that are difficult to reconcile on the premiums front and on the claims front. You just added a whole load of new hassle. These days with technology, you shouldn’t have to do that. You shouldn’t add a little frictional cost. So it’s theoretically possible for a good underwriter to just say, well, I’m just going to be an underwriter. I don’t have to have a balance sheet. I don’t have to have these other things. You know, I can just, because I’m living in a virtual digital world, I mean, we become a virtual insurance company and I just specialize in extracting the value from profitable underwriting, which is what I’m good at. And I can live or die on that. And obviously, it’s not for everyone. But if you’re entrepreneurial and you want to own the equity in that, then you can.

Darren Graves: Right? And we’ll talk a little bit more about technology later. But thanks, Mark. So to educate us a little further, what are the various models that insurance used to partner with MGAs?

Mark Geoghegan: It’s just like a huge kaleidoscope. It’s almost like, if you can imagine it, you can do it. If I wanted, if I was a top underwriter and I wanted to start an MGA, I could just do it on my own. I could go and get a license, I could go and get some backers. I could go and get 10 different insurance companies to back me. And I can show them my track record. But these days, you don’t have to do that. You’ve got people who have set up businesses that are already licensed. They can, they could buy some equity in you. You could go and just plug in and they could do all of your compliance and all that boring stuff and all the regulatory side. They can have all the technology all ready to go for you. They can have all this, and they can even provide all those relationships with the reinsurers up front. And of course, some of them even have their own balance sheet to align that risk. And we’d call those hybrid fronting carriers. So literally, you name it, you can do it, if you can imagine it. And you have different splits of equity, different splits of who does what. But it’s a fabulous ecosystem. So again, it’s just making it easier and easier and easier for that…entrepreneurial underwriters always thought, maybe I should have my own business. Maybe I should own this, you make it so easy for them to make that jump from the balance sheet carrier where they’ve been working all their life so far.

Darren Graves: Yeah, great, Mark. But now to pivot slightly, what are the seated reinsurance challenges associated with MGAs?

Mark Geoghegan: Well it’s a classic. It’s just, how do I know what I’m doing, how do I know what these people are doing down this chain? You know, back in the old days in Lloyd’s in the 60s, you have a hurricane go through the states, through the Gulf of Mexico, and you could take up to 18 months to find out, what has everybody been doing, on this delegated authority on this? Some of these MGAs I’ve been backing, because the technology was so poor. You had bordereau, just with one line. Now, there’s no excuse for any of that. The challenge is to get that data to you. And then probably the real challenge these days is to understand what that data is telling you, and to be able to get the valuable insights that it’s going to be telling you, because, of course, you can have all the data in the world. But if you don’t know what to do with it, so this is a much better look through. You can really, if you’ve got the time, of course, the other thing is to have the resource invest that resource and time in really examining the data that you’ve been given before. Even 10 years ago, you wouldn’t have had this much granular data, but now you can get a ton of it. But of course, if you don’t spend time looking at it, that’s the real challenge. I would say, now.

Darren Graves: Yeah. And excellent. So as a follow-up to that question, how are leading insurers dealing with MGA data quality issues?

Mark Geoghegan: Well, the good thing, that ecosystem there, has known this has been a really big sticking point and a big problem. So whenever I speak to them, they always tell me, of course, and they are, by definition, most of these MGAs are new, so they’ve got no legacy. And so they’ll tell me that, I’ve got better technology than the insurer or reinsurer that’s backing me. You know, because they’ve got the old green screen lurking in the basement, and I’ve got this brand new, on the cloud system. And so they’re almost backing me because I’m, another benefit I’m giving them is I’m actually digitizing them, on their behalf, because, you know, they actually get better quality data from me than what they do from their own underwriters. But I wonder if you’ve got a different view on that?

Darren Graves: Yeah. I think it’s interesting because we, you know, specifically with our reinsurance solution, we work a lot with, hybrid carriers and the biggest challenge, if you would have asked me five years ago, if we were to, market our software to a carrier that deals with 30 MGAs, there’s a huge challenge with that data. Normalizing that data was very difficult. But like you said, with the advancement in technology, that is becoming something that either A) carrier is doing on their own or B) there’s third-party tools out there that they can use to normalize that data and make it consistent for now.

Mark Geoghegan: Yeah, so much money has gone into helping ingest unstructured data, hasn’t it? And you know, bordereau the classic. That’s the classic. And, you know, there’s so much going on in that space. And I’m sure you guys have been really involved in that as well. So again, there’s a ton going on. And yes, I think it’s classic. The MGAs would say that they’ve got better technology, but I’m sure if we had the insurer to defend themselves, they’d say, no, no, well hey, our technology is just as good. And so in other words, let’s be fair. Then that’s great, that’s great for both of you, isn’t it?

Darren Graves: Absolutely, yeah! Great Mark! So we’re already running short on time. But here’s our last question for today: How did today’s market challenges impact insurer profitability and risk?

Mark Geoghegan: Well, I mean, the real key is fuel that reinsurer, that ultimate capital provider, buck is stopping with you. You pay the most amount of commission in that food chain, you have the lowest net premium. And so, ultimately those losses have got to come in under that, that low net premium that you’ve got. And the market itself, we’ve been through a lot of hardening [the] last five years. The market is now coming off that peak. So it’s just, we know that, people are still very happy where we are in the absolute rate adequacy of where we are. We know that most of the business we’re putting on, that people have the confidence that at these prices, most of business being put on the books, is profitable and will be profitable, but they know that the next direction of travel for that premium is downwards, and therefore that just changes your mindset. It’s not all going to be great that, you know, once you’ve decided that tomorrow’s going to be slightly worse than today, maybe not terrible, but slightly worse, you can see the clouds coming towards you. It changes your mindset. So there’s going to be more focus on, ultimate performance of a lot of these MGAs. Of course, some of them are just maturing. When you get into year four, year five, you can really look at those lost triangles and say, all right, okay, is this actually, has this really been worth it? Have they really, all that extra commission I’ve had to pay to get this business? Has it really been worth it? Has it actually provided that net profit for me, because I’m the one who needs this to work. And if I stop, stop it, and if I don’t want to do that, I don’t have to make money, sorry, I don’t have to lose money for a living. That’s not my job. My job is to make money like everybody else. And so ultimately, if I lose money for too long, I’ll, there will be winners and losers, there absolutely always are. You know, not everyone can be top quartile. So some of the bottom quartile will come under more scrutiny, and also the ones that don’t have the quality of data, that don’t have the tech that have got themselves in a bit of a mess because they’ve written a ton of business in a really short amount of time, and they were too busy to have structured it correctly, might have digestion problems, shall we say. And so again, they can be losers operationally as well. So it’s a really interesting time. There will be a little bit more scrutiny, but is still in a good place. But I think everyone knows that we’re getting a time closer to rather than the rising tide lifting all the boats, at the same time. It’s a little bit, when the tide starts going out, you get that classic, you know, that, Warren Buffett-ism saying, you know, who’s been, we find out later who’s been swimming a little more naked than others.

Darren Graves: Right. And I would say, with the advancements in technology, that knowledge is coming faster.

Mark Geoghegan: You’ll know people will have a much clearer idea, much quicker. And then they’ll, right, actually I’m jumping, I’m going to double down on these good guys, because it’s very obvious who the different, the difference between the good guys and the bad guys is much clearer, it’s easier to find out.

Darren Graves: Right, absolutely. Excellent, thanks so much, Mark! You’ve given our listeners tremendous insight into how the MGA reinsurer partnership is transforming the insurance landscape. The $100 billion shift we’re witnessing isn’t just about capital. It’s about innovation, agility, and reimagining how risk is managed in an increasingly complex world. We really appreciate you coming on the show today, and I’m so glad that our podcasts were finally able to collaborate on this special episode. To our listeners, thank you for joining us. We have so much more exciting content planned, and as always, we’d love to hear from you. Connect with us on social media, share your feedback, and don’t forget to subscribe to the podcast so you never miss an exciting and insightful episode. Until next time, this is Sapiens Insurance 360. Thanks for listening!

The post The $100 Billion Shift: Reinsurance’s Booming Relationship with MGAs appeared first on Sapiens.

Mark Sidlauskas: Hi everyone! Welcome to the Sapiens Insurance 360 podcast. I’m your host, Mark Sidlauskas, marketing director at Sapiens. I’m glad that you’re out there listening, this is where we discuss the latest news, trends, and issues from across the insurance solutions and technology spectrum. So let’s get started. AI is rapidly becoming part of our daily lives and businesses are embracing AI to transform processes and drive new levels of automation and productivity.We’re seeing use cases across the industry like in risk assessment, underwriting, claims processing, and fraud prevention, just to name a few. Now there’s a lot of buzz about Agentic AI as the next game changer. With Agentic AI, systems are designed to act autonomously with minimal human intervention and work towards a goal, often interacting with other agents. Imagine AI agents that continuously gather and analyze data from multiple sources like satellite imagery, IoT sensors, public records, and social media to provide real-time scoring.They can automatically adjust premiums, identify emerging risks, and make underwriting decisions for standard policies without human oversight. To help us explore Agentic AI is Denzil Wasson, CTO of Sapiens Decision. Denzel is responsible for Sapiens Decision’s technical strategy and delivery, and brings over 30 years of diverse technology, architecture and implementation experience to ensure customer success. Denzil, welcome to the program!

Denzil Wasson: Thanks, Mark. It’s great to be here!

Mark Sidlauskas: So let’s get started with a bit of history and perhaps you can level-set us. Just a few years ago, decision management was a category and we were just beginning to incorporate AI into our products with Gen AI and machine learning models. So that was converged with decision management into a new AI decisioning category that’s emerged, and that promises enormous value to us. So how did we get from the innovative way of managing rules by extracting decision logic from the underlying technology? And how did that evolve to Agentic AI?

Denzil Wasson: Yeah. So I think that history is important as to where we’ve come from. So for us, it’s a vindication of our vision. We’ve always said that business logic should be treated as a first-class asset and really has a faster lifecycle than the underlying systems, that implement that business logic. So traditionally, the pushing business logic to code, you know, we’ve recognized that really doesn’t work for these highly regulated environments where there’s a lot of contextual difference and there’s potentially fairly rapid change. And so, they imagined the first, the business rule engines, which oftentimes resulted in just about the separation of code and wasn’t really owned by the business and oftentimes resulted in an anarchy of rules became decision management, where the business logic really lived in the hands of the business and the business analysts, and was involved through its lifecycle and published for consumption-based systems. So that’s the traditional business decision management platform that we saw a few years ago. With the advent of AI, you know, the probabilistic decision making, you know, prior to that, all the decision making was declarative and people would essentially do the analysis manually, come up with new probabilities, and then implement those into declarative logic. So with the advent of the machine learning, now we’re able to combine those things. And so we’re able to get the probabilistic items, directly at runtime from the data sets, from the transaction flow. And that’s great, but what do you do with it? You know, if you scored 70, what does that mean? What should I do? And so this is where we see the decision management world and the decision intelligence platforms or decision AI emerging. Because essentially, you need to combine action logic, declarative logic, with the probabilistic logic to actually achieve an outcome. And so the emergence of this new category called decision intelligence platforms is the combination of traditional business logic with AI, both machine learning as well as the new emerging technology of Agentic AI.

Mark Sidlauskas: So if I’m a business analyst and I get a report or some sort of output from an AI model that says the probability is 0.7, what do I do with that 0.7 from the AI system? And I apply my rules to it. And decision says, well, if it’s between point six and point eight, you do X. If it’s in another interval you do something different things. Is that the combination?

Denzil Wasson: Exactly. That’s exactly the combination. We also know that, AI, in the early days where we’re still having challenges around hallucination, you know, there’s still trust concerns around AI. And so AI definitely needs to be combined with other logic in terms of producing an actual action as well as, guardrails, you know, particularly in these highly legislated use cases and industries.

Mark Sidlauskas: So that brings us to AI agents themselves, right? They are tasked with doing these types of things.

Denzil Wasson: Right. So the agents are a significant watershed moment in terms of moving us to the next level. You know, we were an early adopter of generative AI. And in our decision intelligence platform in that we would essentially help the decision analyst, the person responsible for building, logic and pushing it through its lifecycle. We would help them with generative AI, take multimodal sources of natural language documents from their own company policies that say something from the legislators or administrators and even things from the legacy source code. Throw it all into what we called a model AI, which was our gen AI capability, and it would say based on all this information, here’s what I think your logic actually looks like and what you need to do. And then essentially that would become a first-class citizen and they’d be able to push it through its lifecycle. We also combine the ability for machine learning to be in that mix, where you could be provided a natural way to combine machine learning components together with the declarative logic. And you’re in a situation then, where essentially you can say, I’ve applied my declarative logic to decide on the context, which machine learning model should I use? Should I even use the machine learning model? Can I just reject this outright and not incur the compute expense of a machine learning model? And then take that output from a machine learning model and actually reach an actionable conclusion. And that’s where we were pre-Agentic. And so now we’re in a situation where previously, we assisted the analyst and we helped the analyst. Whereas now, we can actually do things with Agentic on behalf of the analyst. So previously, the analyst would take our suggestions and decide whether to implement them and they would take that decision logic through its lifecycle. Now we’re in a position where we can make the suggestions and say would you like us to apply that? Would you like us to do an impact analysis? Would you like us to take this through the lifecycle? Would you like me to generate all the different tests? And so essentially, we’re able to do things. And that’s the difference between agentic and generative, is agentic does things that are actually useful. So in decision, the tooling where we’re introducing agents to be able to essentially do a lot of the commodity work for the human. And then the human is more of a governing body in terms of human in the loop. And then at runtime, when these decisions are actually employed, instead of just producing an outcome that says, oh, yes, you can go ahead and run the policy, an agent can actually be dispatched to go and run the policy. And so the agents are actually doing things for us. Now we’re exposing agents within our tooling, but also the runtime platform will comprise agents that you can call and say, here’s the problem I’m trying to solve. And it will say, oh, this is the packet of logic that you should be executing to solve that problem. Whereas today, we have to know exactly what is my use case, what logic do I need to do. So the future world becomes a lot more dynamic, based on a problem statement that I can define against an ecosystem of agents.

Mark Sidlauskas: So can you walk us through, like a typical problem that someone might encounter? The problem statement of maybe underwriting a policy in a particular state. What would the business analyst be doing and what choices would he be given?

Denzil Wasson: So today the business analyst would have to research and say, what are the rules for this particular state? And they would have to figure out how to model those rules. With gen AI, they would just say kill the rules and it would propose a model. With Agentic AI, they would say, listen, I would like you to propose a model that is taking all of these items. And then I would like you to take that model, and I would like you to generate test cases and here’s some of my criteria around test cases, I’d like you to push that all the way just to pre-deployment, show me all the results of what you’ve got, and then I’ll make the decision as to whether you deploy that amount. And so essentially, the human is just defining goals, constraints and KPIs for the task. The agents are taking care of that and presenting the results to the user for the user to say, yes, I’m good with that, no, I’m not good with that. The user also can decide the granularity of governance. They can say, ask me at every step, or they can say, do the whole thing and then show me what you did. So it’s a completely, variable environment, and it’s really up to the user as to how involved they need to be in the sleep. Obviously, there will be points in the lifecycle that a human has to review [at] this point because AI is where it’s at. And then I think once, what’s really exciting, not only from the design time point of view, but from the runtime point of view, the fact that today, we might have KPIs being monitored and then eventually a monitoring of a KPI results in a change coming from a requirements perspective through the lifecycle. And that could take can take weeks, could take months for that to happen. With the agents, not only are they listening and recognizing there’s a KPI that can actually do something with it. And so that makes the new one a lot more exciting in terms of being able to change those cycles, because remember, originally our goal was to extract business logic as a separate asset to be able to accelerate its lifecycle. And now we’re looking at doing that even faster with automation from agents.

Mark Sidlauskas: So if I’m, let’s say in the mortgage industry and interest rates drop where some change happens in the market, I could go, I could tell my agent, change the loan to value ratio so I can extract more from the market, or less depending on my risk profile, and it would execute that immediately.

Denzil Wasson: Yeah, I think it executes it immediately. I think what’s really interesting is that change could potentially ripple through to other agents. And another agent could be going through your servicing book and saying, we should make an offer to all of these customers. Because you changed that, and so the causality and how things happen is going to be a lot more exciting in terms of optimizing and instead of us saying, oh, because of this, we should think about that. You know, we have the agents that essentially will be proposing to us, you should do these things, do you want to do them? I can make the change for you, would you like to do it? And then we’re in a world where we can feed back and say, [I] kind of like what you’re suggesting, but maybe tweak this and that and then present that use case to me again, and the agent does it, and then we say, yes, let’s do that. And it goes away and does it.

Mark Sidlauskas: So I would have the appropriate guardrails in place to make sure that if I don’t like it, if it’s going to cause me any damage, any business risk, I can shut it down or guide it to the right decision.

Denzil Wasson: Yeah, I think that’s always important. You know, at the end of the day, the agents and in today’s world are using tools, and those tools are some implementation that is doing something. And when to use a tool, when, which agent to use, when, and what the tools should do, are all going to be governed by logic, by some business logic and some in some way. You know, I may look at the service book and say, let’s make an offer to all these people. But someone needs to say, well, let’s not do that to mortgages that we’re busy foreclosing on, as an example. And so you have to have some kind of constraints around the logic.

Mark Sidlauskas: So as we move further up to the future, we’re optimizing around the system and then maybe systems and across a huge ecosystem, potentially. Where do you see the future or what’s the future vision for AI decisioning and Agentic AI?

Denzil Wasson: Yeah. So I think the agents are going to get more powerful, their tools are going to get more powerful. I think that the trust is going to evolve. You know, the more structured use cases will reach a point that the agents become more reliable. And as they become more reliable, we can give them more autonomy. And so essentially, it means that our work is going to be a lot more creatively focused and a lot less on the commodity page today. It’s almost like we’re going to have assistants that are saying, I’ve figured out this whole idea, here’s my presentation. Do you like it or don’t you like it, and then what would you change? Whereas today, we have to do all of that ourselves. And so I think it really allows us to offload commodity work, allows us to be more creative. And I think that creativity, I think for a lot of organizations, essentially is going to result in a hyper-personalization of the offerings, where because we have the ability, the agents, the ability to make changes very quickly. I think that companies are going to have opportunities to really please their customers.

Mark Sidlauskas: Yeah. I think it takes personalization to a very much next level. We’re seeing that right now. So this could take us to places that we hadn’t even thought about before.

Denzil Wasson: Yep!

Mark Sidlauskas: So thanks, Denzel! It’s fascinating to see what’s going to happen here. And we should get together for another episode maybe in six months, probably sooner, because things are changing so rapidly!

Denzil Wasson: Absolutely. Yeah. [Our] agents can get together.

Mark Sidlauskas: Yeah, exactly. Mine will call yours. To our listeners, we have more exciting content planned as always, we’d love to hear from you. Connect with us on social media, share your feedback, and don’t forget to subscribe to the podcast so you never miss an episode. Until next time, this is Sapiens Insurance 360. Thanks for listening!

The post Agentic AI: The Next Wave in Insurtech? appeared first on Sapiens.

And that’s just an amazing mission. Thank you for that, Brian, and thank you for joining us. Welcome to the podcast!

Brian Steiner: Thank you, Chris, it’s great to be here. Really excited to chat with you and appreciate the invitation to be part of your program.

Christine Burke: Okay. So, let’s dive right into it then. Brian, can you tell us a little bit about the importance of having a personalized, interactive digital experience, in particular in today’s world of multi-channel experience in terms of reaching customers about the need for life insurance?

Brian Steiner: Absolutely, Chris. You know, I think, we need to meet consumers where they are and how they consume information and where they do it. And it may be in multiple places, depending on the type of information they’re looking for. But it’s important to understand the, the strengths of, of media and how they’re learning and what’s best suited.

So as a nonprofit, Life Happens, our focus has always been on education and storytelling. And the conversion lies with the companies. But remember, consumers are not going to buy what they don’t understand. And, for Life Happens, we focus on social media, which we find to be an extremely effective method, mostly because it can be easily shared and amplified. And we use our website and YouTube for a longer format. And then we spend a lot of time on Facebook, LinkedIn, Instagram, TikTok, to help share information around the importance of life insurance and other protection products. And, for companies, this is going to look a little different. Because of the conversion, but we start in the same places for the majority of people. But helping them understand what life insurance is and why they need to buy it. Again, people don’t like to talk about getting sick, dying, and getting hurt. So it’s important for us to find ways through those different media outlets and social platforms to engage in story tell and get people to really understand the impact, that those products and services can have on their lives.

Christine Burke: Right. And the companies to your point, really need to be, and all of those, all of those channels as well, to while you’re educating them and then they can go to reach those companies through those various methods.

Brian Steiner: And we’ve been doing this study with LIMRA going back 16 years called the Insurance Barometer, where we’ve been, you know, doing research on consumers buying habits and perspective on the industry. And at that point in time, it was something like just under 30% of folks were spending time online or going to social platforms for their financial information. [Our] Recent report and study shows that that number is now over 60% and on the rise.

Christine Burke: Wow.

Brian Steiner: So this isn’t necessarily specific or just isolated to like Gen Z and Millennials, which is even higher. But, you know, the Baby Boomers and the older demographics, they’re playing in that sandbox, too, for their financial information. And, you know, as a, as a nonprofit organization that their focus is educating consumers. You know, we’re doing our darndest to try to meet them where they are and be visible on those platforms and be a trusted voice through those platforms, about the industry, the impact, and the need. So, you know, companies, there’s with insurance companies, there can be a little lag. Or maybe they’re a little bit more risk averse in their approach and activity on those platforms. But, you know, an organization like Life Happens, we can be, a little bit more flexible in that regard. And really, that’s where we’ve aligned our resources, you know, to kind of meet consumers where they are and be that trusted voice.

Christine Burke: You mentioned your barometer study. I know there was an interesting stat that said that people overestimate their life insurance costs by 7 to 10 times than what they actually are, which is amazing to me. How do you think this misconception really affects the impact of even the most sophisticated digital platform out there by industry or by insurance companies?

Brian Steiner: Sure. And, you know, I mean, it’s not just the pricing misconception. There’s a number of misconceptions out there. And the impact is it makes people think that they can’t afford the products or services or promise them to put it off or ignore it, it’s not for me, when really these are important conversations to be had. Again, it’s not something that people wake up in the morning and, and probably think about that regularly, like, I need more, I need my life insurance today or I have life insurance from work, and I don’t need my own individual policy. But understanding that these products are affordable and can be affordable and there’s different types and, you know, pricing can be different from the type of insurance that you decide to move forward with. But, you know, getting people to realize that taking action when they’re younger, can really make all of these products a lot more affordable and accessible. And, we’ve got some great resources off the Life Happens.org website that are needs calculators that help people understand, you know, the type of coverage that might be appropriate for them. But also, you know, how they might want to scale in the future as they’re, as they get married or have children or the family grows or they own a business or what their liabilities may be. We’re always out there trying to get people to act sooner. There’s an analogy about when’s the best time to plant a tree. And a lot of times it’s ten years ago or today. And, the same can be said for life insurance. Getting people to understand that just because, you’re, you know, a younger generation or maybe you’re not married and you’re single, going through that process and locking in your insurability when you’re when you’re young and healthy, can save you lots of dollars down the road.

Christine Burke: Yep. So what’s interesting too, is in your, in your study, it mentions that the Gen Zer’s, the people who out there who won’t get their phone out of their faces, even at the dinner table, they still want to, you know, once they get the insurance information, okay, they’re ready to purchase. They want to purchase with a human being, which, again, I find that fascinating. So talk a little bit about a human, how a human interaction still matters in the life insurance purchasing process.

Brian Steiner: Sure. And as you’re talking about being locked into your screens, my daughters were fighting over iPad this morning before we went to school. So, I feel like that resonates really well because, while so many people, again, are on social platforms for information, financial services, insurance and all the things, the conversation around life insurance and I think disability, long-term care, whatever it may be, these are pretty personal conversations. And I think, you know, how we educate and story tell can get people to think differently. But I think the role of an agent and advisors are incredibly impactful, because I think it can help get people across the finish line.

Christine Burke: Yeah.

Brian Steiner: There’s always going to be those folks that, you know, are going to want to, you know, go through that process virtually through an online platform. And that number probably will continue to grow. But there’s still always going to be, I think, a pretty large segment that kind of want their hand held through that process at the end.

Christine Burke: Yeah.

Brian Steiner: [To] Make sure they’re making the right decision. There’s so many different nuances and so many great products out there that yeah, you know what, a social or a needs calculator can help me say, you know what? Yeah, I need x amount of coverage or, you know, can make a recommendation. But when the rubber meets the road, I think getting people to act and again, people don’t like to talk about getting sick, dying, and getting hurt. It’s an easy thing. It’s an easy conversation to kind of dust under the rug or kick the can down the road, or whatever analogy you want to use in that moment. But the agent and advisor can help how we kind of, you know, kind of like a workout buddy, like an accountability partner in this to get people, you know, to say, hey, you’re doing the right thing. This is really important. Let’s put this in place. We don’t know what’s going to happen tomorrow. And regardless of walk of life, how much money you make or don’t make, I think everyone deserves access to professional advice if they want it.

Christine Burke: Yeah.

Brian Steiner: And there’s a lot of great resources out there, and we talk about NAIFA, the National Association of Insurance and Financial Advisors. If you want to connect with a professional, you have the ability to do that through LifeHappens.org, find an advisor and all those folks are part of the NAIFA professional association, and I think it helps get people across the finish line.

Christine Burke: Great! [I] totally agree with that one, me being a Gen Xer, so I, I will agree with that one. But, you know, we’ve been talking a lot about the social media and how you mentioned six in 10 people are using social media for, for research on insurance. And I know that Life Happens has been working with influencers and platforms like Instagram and Facebook. And I know insurance companies have a little bit of a concern balancing compliance and then how to use these platforms to reach their consumers. So what’s, how can insurance companies, you know, figure out that balance between the two, between compliance and working on these new, you know, not really new platforms for that?

Brian Steiner: Yeah. And Chris, obviously with Sapiens, in your organization, you understand the importance of, kind of digital transformation.

Christine Burke: Yep.

Brian Steiner: And we also are in an industry that, you know, isn’t always the most progressive in that regard.

Christine Burke: Exactly!

Brian Steiner: You know, there’s a lot of change that’s needed. Change in this industry takes time. You know, it is it tends to be, it is a risk-averse mentality.

Christine Burke: Yep.

Brian Steiner: And that’s not to say that we have, they have to overhaul their compliance functions in order to, to be more active in those platforms. But, you know, we’re trying to work closely with our carrier partners to be a resource to show them the impact that they can have on these social platforms and be more active. You know, sometimes when these groups post and there’s a number of insurance companies that are, have gotten really good and they put out some really great stuff. But there’s also a lot of others that, aren’t as active, aren’t as willing. And you know, we try to work in collaboration to say, hey, if you’re trying to meet consumers where they are, or target a specific demographic, you know, you need to rethink your approach a little bit. And we, from our perspective at Life Happens, we do a lot of testing with these companies. If they want to see how a message resonates in a certain space, we tend to be or can be kind of that barometer for them. And give them the feedback to say, hey, this resonated this didn’t, you know, you might want to think about, you know, being active here in this market, you know, on TikTok or Instagram Live or whatever it may be. So I don’t want to say that we’re holding hands. But we’re doing our best to collaborate and, get them to, to realize the impact that those channels and platforms can have on consumers.

Christine Burke: Great! And, you know, whether they like it or not, social media is here to stay. So we’ve all got to embrace it, even the big guys, right?

Brian Steiner: Absolutely. And there’s again, this actually kind of feeds in where at Life Happens, in coordination with LIMRA, we’re about to release our second iteration of our insurance barometer study, which really focuses in on, life insurance in the misinformation age. And establishing yourself as a trusted voice, through those platforms, is really important because there is so much misinformation out there. And we want to work with organizations like yours and all the carriers to make sure that the content and what people are you know, what’s being put in front of them or what they’re digesting is, is accurate and relevant. And is representative of the good work and impact life insurance and agents and advisors can have on, on themselves and their families and their businesses. So, we’re excited about that next wave, we’re excited to be, to serve a key role, in this industry to educate consumers and spread the good word.

Christine Burke: Excellent! Well, as you mentioned, you’ve got that new report coming out. So everyone out there, please make sure to visit the Life Happens website to learn more about all of their research and how they’re educating the public, and to donate or learn more about their scholarship program. I want to thank Brian again for joining us. 

Brian Steiner: Thank you, Chris!

Christine Burke: You’re quite welcome! As always, connect with Sapiens on our social media platforms. You can share feedback and subscribe to our podcast. If you’re not a subscriber already so you don’t miss an episode. But until next time, this is the Sapiens Insurance 360 podcast. Thanks for listening!

The post Beyond Digital: Creating Personalized Insurance Platforms appeared first on Sapiens.

There’s the famous saying, often attributed to Benjamin Franklin, that nothing in life is certain except for death and taxes. With apologies to Ben, I’d like to add to that insurance bills for most households, for the purposes of today’s podcast. And let’s face it, most people aren’t exactly excited when receiving their insurance premium bills and become much less so when they’re faced with a lack of modern payment options. Most insurance carriers today are under growing pressure to modernize billing and payment experiences for their policyholders. And in today’s podcast, “The Need to Modernize Insurance Billing,” we’ll explore the key challenges, emerging trends, and digital tools reshaping how insurers engage their customers from self-service options to flexible fee models. And with me today to discuss the topic is Rob Eberly, Vice President of Sales at Paymentus, a Sapiens partner and leading provider of cloud-based bill payment technology and solutions.

Rob has 15 years of experience in electronic billing and payments, cultivating deep partnerships with market leaders, including many top utilities, insurers, and communication service providers. Throughout his time at Paymentus, he has remained focused on payment modernization strategies while maximizing the consumer experience to drive electronic payment adoption. Rob, welcome to the program!

Rob Eberly: Thanks, Alex. Happy to be here! And thank you for the warm introduction!

Alex Presley: Absolutely, Rob. Now let’s jump in. So, set the stage for us. What have been the barriers for insurance carriers historically in terms of meeting policyholders’ demand for more modern and flexible payment options?

Rob Eberly: You know, Alex, it’s a good question. I think there’s a few factors at play here. So if you think of some of the historical payment providers that insurance carriers might work with, you’re looking at legacy payment providers, maybe with outdated technology, maybe tech that maybe didn’t have the nimble capabilities to leverage innovation and deploy more modern capabilities. So part one I think has to do with the payment relationships that they’ve had historically. But even before that, you know, I think it comes into managing their own homegrown, back-end systems, right? I feel there’s many carriers out there that either have homegrown systems or numerous different divisions and product lines that have different back-end systems that maybe they acquired or inherited through an acquisition. So there’s a lot of, a lot of fluidity in that relationship in terms of what they’re using in the back end and outdated technology. So, you know, kind of back to you, Alex. I suspect that’s something that you see at Sapiens and quite often in terms of helping insurance carriers upgrade their core systems.

Alex Presley: Yeah, that’s exactly right. It’s something that we see time and time again. You have carriers running on legacy systems. Makes it difficult to plug in new payment channels or fee models. And when Sapiens steps in to replace or modernize those cores with, you know, modular, API-driven systems, insurers suddenly have this flexibility to integrate these best-in-class payment solutions.

Rob Eberly: Yep, I think that’s what we do, right? And sorry to cut you off. I was just going to suggest that it’s kind of a, a two-pronged approach, right? Step one ensures that [they] get an appropriate upgraded back-end system. And then step two, that can start to leverage some of that new technology. So it goes hand-in-hand.

Alex Presley: Yeah, absolutely. That foundational upgrade is what unlocks those self-service portals, those flexible installment plans, and the real-time billing insights, which is what today’s policyholders expect. So moving on, how are insurance carriers evaluating their capabilities against peers related to billing and payment, and how do they ultimately interact with their customers?

Rob Eberly: You know, Alex, I think [number] one, they are focused on peer comparisons. They’re looking from a geographical proximity perspective. They’re comparing themselves against peers of similar product lines, maybe in similar size from a net written premium perspective. But I think they’re also comparing themselves against, against the Amazons of the world, against telecom providers, against other verticals that are leveraging best-in-class technology. You know, I think they’re certainly looking to confirm what their peers are doing in the insurance world and making sure that they’re not losing out on customers based upon maybe having a lack of capabilities. But I think there’s also a realization that there’s an opportunity to deploy more nimble capabilities and expand how they interact with their customers. And really, I think we’re seeing a lot of momentum from insurance carriers doing just that right now. And leveraging the template or technology.

Alex Presley: Yeah, it’s a great point. While carriers often start measuring themselves against regional peers offering similar products, I think the real benchmark today is in any seamless payment experience consumers enjoy from Amazon or their mobile carriers. Once insurers see those on-demand flexible billing journeys, they know their legacy systems are holding them back. Modern API-based cores empower them to quickly deploy the same smooth, self-service payment options that keep customers happy and loyal. So okay, so to my next question, to pivot slightly, what are the most common trends insurance carriers are evaluating, as it relates to billing and payment in terms of channels where they interact with customers and different fee models they may be evaluating?

Rob Eberly: So this is a great question and something that quite frankly, could be an entire podcast topic in and of itself. First, there’s a heavy focus on web interactions and trying to drive self-service with single customers. What can insurance carriers do to eliminate calls to their CSRs, to help drive self-service? So those unneeded billing- and payment-related questions don’t result in a call to their contact center. They’re looking to drive paper suppression, reduce reliance on paper, shift to digital. And just making sure that ultimately, they create these avenues based upon where these customers want to interact with. It’s over the web.  It’s auto pay, one-time payment capabilities, text, chat, you name it. The importance is just really having a broad approach of where they can interact with their customers to help drive self-service. So that’s point one. Point two, and this is really a massive focus amongst insurance carriers, is the topic of introducing user fees or surcharging, essentially charging a fee to the consumer if they pay with a credit card, where a user can still make a payment for at no cost, using debit and debit or ACH. But introducing that fee on a credit card payment is a massive cost-savings opportunity to reduce their card-processing expense. Customers are familiar with user fees today, and Alex, I suspect you probably see this in your everyday life, right? Where user fees are tied to everyday transactions.

Alex Presley: Yeah, absolutely. I see those user fees everywhere. You know, in the service charges on concert and event tickets, the small credit card surcharges at restaurants and, you know, even the extra fees plumbers or electricians tack on for card payments. Consumers have come to expect them, I think, to a certain degree, which, you know, makes it a natural fit for insurers that are looking to offset some of those costs.

Rob Eberly: And I think that’s exactly it, right? User fees are everywhere, you can’t avoid them. Customers are familiar if they’re paying their utility or telecom bill, there’s already likely a user fee attached to that. Insurance is no different, and insurance carriers are just now starting to be able to leverage that user fee as one of the largest cost-savings opportunities that they have. And to realize that they can do this, they can do it in a compliant manner, they can do so without disrupting or negating the customer experience. You know, you combine this opportunity to modernize their billing and payment strategy, their approach to billing and payment, while driving material cost savings. That’s become a very powerful equation in terms of how our customers are evaluating project prioritization. It’s really bumping up this billing and payment strategy evaluation to the top of the list, when you can also drive significant savings.

Alex Presley: Yeah, absolutely. It’s a great opportunity to just increase the value that these modernization projects provide to insurance carriers. Okay, so to look at it from a more modern technology perspective, what can insurance carriers gain after implementing more self-service options like chatbots and text payment? What other channels might they be considering?

Rob Eberly: So I think there’s a common theme process, right? You know, much of this is meeting customers where they would pay. Different individuals have different preferences in terms of where they want to pay, how they want to pay, with which instrument. And the more that they can meet the customer where they want to pay, you drive positive customer sat, you increase collections, you reduce late payments, there’s a positive effect across the board. So you mentioned a few of the channels, being able to pay for a PCI-compliant, AI-based chatbot is one, engaging with text pay. You might have customers that want to make a payment through their PayPal app. PayPal has a bill-pay component and have that transaction posted to the insurance carrier in real time. But separately. you know, we hear from many insurance firms that we know, the fact that there’s a subset of customers that have not only an interest, but a need to pay in cash. And some insurance carriers get cash in the mail, still. They’ll get cash at an agent location and it becomes a nuisance. So the idea that an insurance carrier can have a customer walk into any Walmart, CVS retail location, approximately 90,000 locations in total, make a payment in cash posted to them in real time through an existing integration with Paymentus, is a powerful thing. So again, our interest is expanding where they can interact with customers. At what location? Through what payment method, maybe using a digital wallet, or maybe through tech, maybe it’s through chatbot. But the more that they can expand how the customer will interact with them, the more they can increase collection, reduce late payments, increase positive customer experience. It really has, [a] positive impact across the board.

Alex Presley: Yeah. It’s impressive how expanding, you know, beyond web and mobile into chatbots, text payments, the cash in network locations and even PayPal. It creates a truly omnichannel experience in order to meet every customer, you know, where they’re at on their preferred, turf. So by offering all these touchpoints, carriers are not only driving digital engagement, but they’re also, you know, boosting collection and minimizing a lot of those late payments.

So, Rob, based on your work, which of these emerging channels has delivered the biggest surprise in terms of uptake or ROI for insurers?

Rob Eberly: I think the largest trend that we see right now is within digital wallets, and the fact that customers are interested in paying with them from security, from a convenience, from a familiarity perspective. So I think that’s one. But I think the biggest, the biggest power behind all of this is not having to be tied to one of these channels, right? One of these channels or methods in the fact that you can deploy all of them and it can be done without it being a time-intensive project for our insurance carriers. Digital wallets are a massive opportunity, but I think the strength is in having numerous different channels available for customers to pay.

Alex Presley: Absolutely. Okay, Rob, one final important question. To ensure peak performance of all functions, what are the top considerations insurers must not overlook when evaluating their billing and payment strategies?

Rob Eberly: So we spent a lot of time talking about modernization. And I think feature functionality and innovation are huge factors when evaluating payment strategy, maximizing customer engagement, increasing revenue collection, driving a positive customer experience. That’s one factor to the equation, but it’s not the only factor. I think when you look at deploying change and making sure that you can get to market quickly with change and deploy change via configuration, and also having continuous innovation, right? Because it’s one thing to modernize for your needs of today. But insurance carriers are looking to modernize for next month, six months, next year, five, 10 years down the road. So partnering with a, partnering with a provider that can help you on that journey throughout, you know, as payments are continuing to evolve is crucial. And lastly, it’s also the stability of the platform. So you can have a modern, modern payment strategy, payment environment, deploying change quickly, but you need to ensure that you have a stable platform. When a customer needs to make a payment, the payment experience needs to be there, it needs to be reliable from a customer-facing perspective and also in terms of, your internal operations. So there’s not really one single factor that I would suggest moves a needle, but an insurance carrier needs to have a strategy. And all of these kind of work in concert to drive that cohesive strategy. So billing and payment modernization is a major opportunity for insurance carriers. But they need to look at the entire picture when they’re evaluating that strategy.

Alex Presley: I think you’ve hit the nail on the head, Rob. Insurers need to juggle, you know, all of those pillars together, and when they strike the right balance between functionality, speed to market, and reliability, they set themselves up, you know, for stronger collections, happier policyholders, and a more efficient, back-office process. So, Rob, you’ve given me and our listeners a lot to think about the next time we have to go pay a premium, and certainly made the process sound much less onerous, especially when coupled with a modern and streamlined payment solution. I’m sure Ben Franklin, quite the inventor himself, would be impressed.

To our listeners, thank you for joining us. We have so much more exciting content planned, and as always, we’d love to hear from you. Connect with us on social media, share your feedback, and don’t forget to subscribe to the podcast so you never miss an exciting and insightful episode. Until next time, this is Sapiens Insurance 360. Thanks for listening!

The post The Need to Modernize Insurance Billing appeared first on Sapiens.

Paul Applegate: Larry, it’s my first podcast as well, but, I think we can get through it together. Let’s give it a shot.

Larry Stern: All right. Sounds good. I’ll introduce you in a second, but let me first set this up. Today we’re talking about ecosystem partners. Sapiens has over 250 partnerships with innovative companies that help us meet large, complex implementation challenges. And one of our valued partners is InvoiceCloud, who’s a leader in electronic bill presentment and payment technology, that helps us simplify complex payment processes and drives digital adoption.

Today’s guest is Paul Applegate, VP of Alliances at InvoiceCloud. Paul has been with InvoiceCloud for four and a half years and has built up a strong partnership ecosystem, which now encompasses over 70 active partnerships. Prior to joining InvoiceCloud, Paul held leadership positions at fast-growing companies like LLamasoft and Opower, while spending the first half of his career at companies you’ve probably heard of like SAP and Oracle.

Did I get that right, Paul?

Paul Applegate: You did, Larry. Thank you very much for the kind welcome. The one thing I’ll add is that, I’ve been at this for a long time. I’ve been working in and around partnerships of varying shapes and sizes for the last 20 years. It’s still the thing that gets me really excited. And so any opportunity like we have today to talk about the power of a great partnership, is time well spent. So really excited to kind of lead in with you today.

Larry Stern: Great. So let’s start by chatting a bit about Sapiens’ and InvoiceCloud’s, working relationship and successes. I think the headline is that when integrating with you, we drive 40% more on-time payments for our joint customers.

Paul Applegate: Yeah, it’s a great stat, Larry. It’s one that we’re really proud of. And I think about, kind of how we talk to CFOs about this. And so when we, when we first engage in organization and we lead with that stat, it gets folks really excited. So you think about the possibility of what that means to your organization from a cash flow perspective. Eliminate unnecessary policy terminations. You know, these are things that across the C-suite, things people get really excited about. The next question, and this is where we kind of really get excited, is when we’re able to kind of dive in and talk about how we do this. And part of how we do it is, is through a great joint story that we’re able to tell together. Primarily because we built a great integration, between Sapiens and InvoiceCloud.

Larry Stern: Right. Where you said from a CFO perspective, that’s the business perspective. This is a technology solution. So let’s pivot for a second to the CIO perspective. What are some of the biggest challenges carriers face when implementing modern cloud solutions to replace legacy solutions? And how can strong partnerships help us to overcome them?

Paul Applegate: Yeah, I think it’s a great question. And I would kind of tease it apart and talk about it in two different ways. One is the cloud portion of that. So every CIO that we talk to, every CIO that you see interviewed, every CIO poll that’s out there says that, yeah, they’re thinking about a shift to the cloud.They’re on some kind of progression to the cloud. But what happens, and I think this is the second part of the question is, there’s so much legacy baggage around big hairy technology projects. The CIO has become a little bit scared, right? In the past, they’ve been burned by projects that take too long. They spend thousands of hours getting them up and running, hiring internal external resources.And so it becomes really important to be able to tell a story, like the one we have together about an integration that’s pre-built, that’s proven, and will help them deliver value within six months. And we go in and we tell that story together. All of a sudden, it’s a different type of conversation. And folks are really able to kind of leverage the power of the cloud.And when I talk about the power of the cloud, I’m talking about specifically this lack of technology drag, for example, everyone on the planet is on the same version of Netflix, right? That happens seamlessly. It happens behind the scenes. And so when I think about a true SaaS offering like InvoiceCloud being integrated to Sapiens, that’s the kind of power that I’m talking about. And luckily, we’ve been able to tell that story successfully across the market, and we really welcome the opportunity to talk to more CIOs about it, as they think about their technology roadmap.

Larry Stern: Yeah, that makes sense, Paul. You mentioned integrations. How do tight integrations between partners contribute to a better customer experience, particularly when it comes to policyholder interactions like billing payments?

Paul Applegate: Yeah, it’s super important. And so, when we think about kind of what we’re doing here with our organizations, we’re taking data from Sapiens around, the premium route to, and we’re pushing out electronic communication that drives folks to pay, so that has to be real time, right? We never want to put our customers or our customer of customers in a situation where they’re seeing incorrect information. So [I’m] really proud of what we’ve built there. If we take it a step further, the real value that we deliver is in and around the design of our platform. So, you know, meeting customers when and how they want to engage is table stakes. So we offer all of the modern payment solutions so folks can leverage Apple Pay and Google Pay and Venmo and PayPal. As I said, we think that’s kind of, a very low hurdle to get over. What happens when you kind of take the next step that is, to drive behavioral change through that interaction, that’s where it really starts to get interesting. We couldn’t do that if we didn’t have that joint integration with you. And so what we’re able to do is allow insurance carriers to really seize on that moment when their customers are fully engaged, that is, when they’re paying their premium to not only meet them how they want to pay, but also, as I mentioned, get them to do something different. And so that might be sign up for autopay, sign up for pay by text, sign up to stop receiving a paper bill, and this has a huge business impact on our own customers.

Larry Stern: Yeah, that that totally makes sense, Paul. So from your perspective, what strategic advantages do insurers get by investing in ecosystem partnerships, rather than building it all in-house?

Paul Applegate: Yeah, it’s a great question. And I think I’m going to break a podcast rule here, Larry, and I’m going to flip it back on you. As a senior leader within Sapiens, you know, you and your organization are faced on a daily basis with really hard decisions. And one of them is, is always do we build something or do we partner? And so I’d love to kind of hear, you know, about your thought process. You know, why we decided to partner with a company like ours instead of trying to build your own solution, which, unfortunately, we’ve seen other organizations try to do and fail.

Larry Stern: Yeah. You know, the insurance, the whole industry and the ecosystem has changed so much, Paul, over the years. And thank you for giving me time to actually think about my answer here. When I started in insurance, I think all of the processing, the data resided within the four walls of the company, that’s just not possible anymore today. You know, even though the largest insurer or biggest software company couldn’t build everything in house, there’s too much innovation happening out there in the marketplace. And if insurers want to stay competitive, they’re going to need to take advantage of that. You know at Sapiens, we provide great core insurance solutions. But we need to enable our clients [to] easily take advantage of all the innovation happening in the marketplace. I think that’s the only way we stay relevant, into the future. So we’ll keep growing our partner network. We’ll allow our clients to leverage new capabilities and to swap in different capabilities, when it makes sense for them. You know, you’ve been providing and developing payment solutions for 15 years now. You know, why would any insurer or software provider try to replicate that? That just wouldn’t make sense. So, you know, to remain dynamic, to remain competitive in the marketplace, I don’t think it’s an option anymore. It’s a necessity.

Paul Applegate: Yeah. I love that answer. I’m going to steal part of that next time. somebody asks me a question similar.

Larry Stern: Okay. Paul. So maybe, a final wrap up. Could you talk a little bit about how our clients are always in kind of a modernization and transformation journey? And how together, Sapiens and InvoiceCloud can integrate ourselves with and successfully drive that transition?

Paul Applegate: Yeah, I’d be happy to and I heard something the other day and I’m going to repeat it. And I’m not going to be able to attribute the quote to somebody. But we’re at a point now, today being, we are at the slowest point of transformation that will ever happen in the future. From this point forward, transformation is always is going to accelerate. It’s going to accelerate on a daily basis. And so, when I think about, you know, this push for modernization, we as consumers aren’t discerning anymore between who’s providing us technology, who’s providing us a window into the technology that we want to work with. And so I’m not discerning between my insurance carrier and applications like Uber and DoorDash and Amazon. I need them to be intuitive. I need them to be easy to use. And in some cases, if they’re well designed, I’m going to allow them to change my behavior. And so when we think about that, it’s not an option for insurance carriers to kind of stand back and be fast followers. They really have to dive in and embrace technologies. They’re going to allow them to meet their customers when and how they want to engage. And by using a technology like InvoiceCloud, that’s sitting on top of Sapiens, not only can they do that, but they can all, they can also leverage that moment when their customers are fully engaged to drive real business values through behavioral change. And so, we’re excited about, what our peers on the retail side are doing, because it puts more and more good pressure on all of us to build better solutions, that have real-time integrations that are intuitive to use, and really allow our customers’ customers to interact with us in a way that they choose. And so, I think about our partnership and where we come from. I’m really excited about our history together, but I’m even more excited about kind of where we’re going at this really important inflection point for, for our customers.

Larry Stern: Well, talk about stealing, Paul. I’m definitely going to steal that, slowest, slowest ever part of transformation from you. I think that’s a great quote. I think it’s a good point to just say thanks for coming on the show today to speak at length about the value of partnerships and how our collaboration can really power successful core transformations. Of course, I’d like to drill down a little bit more into the Sapiens and InvoiceCloud partnership and what that’s meant to our clients. I’m sure we could have another whole conversation about that, given our ongoing and expanding relationship. So definitely something to consider. Maybe we’ll do that, six months from now.

Paul Applegate: Oh, I’d love to do that, Larry. And I’m really looking forward to seeing you and your team here in a couple of months.

Larry Stern: Yeah. We’ll be together at the Biltmore, in Arizona for Sapiens’ client conference. It’s going to be a great event. And I thank you for doing this, Paul. And I’ll buy you a drink when we get there!

Paul Applegate: That’d be outstanding. Thanks, Larry!

Larry Stern: All right. To our listeners, if you’d like to learn more about [the] Sapiens/InvoiceCloud partnership and the value that each organization brings to the relationship, check out the links in the episode description. And as always, connect with us on social media, share your feedback, and don’t forget to subscribe to the podcast so you never miss another insightful episode. This is Sapiens Insurance 360. Until next time, stay curious and thanks for listening.

The post Driving Insurance Policyholder Innovation Through Partnerships appeared first on Sapiens.

Ask the average person on the street about what they know about insurance, and it’s safe to say they can give you a fairly accurate description. Every month I shell out hundreds of dollars for my home and auto policy premiums. And the insurance industry is constantly featured in the news whenever there is some catastrophe like a hurricane, wildfire, or flood. So people understand the role of insurance and its purpose. I mention the concept of reinsurance and most people draw a blank. So what is reinsurance and how does it relate to insurance? And what is the need for reinsurance in today’s markets? Here to answer that question and provide us with more information about the need for reinsurance is Sapiens’ VP of Reinsurance Business Development, Craig Robinson. Craig, you were last on the show talking about claims leakage, another key topic in reinsurance. So it’s great to have you back for another session and welcome!

Craig Robinson: Thanks, Mark. It’s great to be back on the program. I don’t think I would have remembered my earlier spot on the podcast if you hadn’t reminded me.

Mark Sidlauskas: How could I forget, Craig? So let’s turn to today’s topic. In a nutshell, how would you define the concept of reinsurance?

Craig Robinson: Well, reinsurance is basically the insurance of an insurer, right? So it’s a financial arrangement, which [the] insurance company, which we call a ceding company or primary company, transfers a portion of its risk to another insurance company, so that’s called the reinsurer. And this is done to reduce the potential for large losses, to stabilize earnings, and increase the insurer’s capacity to underwrite more policies. There’s a couple types of reinsurance. One is treaty that covers a group or portfolio policies. And then there’s another one called facultative, which covers a specific risk, an individual risk, or a policy.

Mark Sidlauskas: So another basic question, what does reinsurance accomplish? Is it simply risk transfer? And how does it differ from regular insurance?

Craig Robinson: Well, risk transfer is central to what it accomplished, but it’s definitely not the only item that is accomplished by reinsurance. So, I mentioned the risk transfer before, about transferring risk from the insurer to the reinsurer. But there’s also capital relief and solvency protection. There’s capacity expansion, there’s earnings stabilities, and one that’s often forgotten is just access to expertise, because reinsurance companies can provide actuarial underwriting claims expertise, which is very helpful to emerging risks and lines such as cyber that companies are getting into.

Mark Sidlauskas: So let’s pivot to the different types of reinsurance. Is reinsurance limited to just the property and casualty carriers?

Craig Robinson: No, no. Reinsurance is not just for property casualty, but it’s also utilized by life and health insurance companies. For instance, reinsurance in the health care sector allows health insurance providers to manage risks that would be challenging to handle on their own, especially when handling, you know, individuals with preexisting conditions and things like that. So, I deal mostly on the P&C side, but there definitely is reinsurance for life and health carriers.

Mark Sidlauskas: Okay. So you’re in the market every day talking to clients. So what do you see as the major challenges that insurance companies are facing running their reinsurance programs?

Craig Robinson: Oh, yeah. There’s a wide variety of issues that they’re facing. One has to do with just inflation and economic volatility. So, you know, high inflation affects the cost of claims, makes it harder to price reinsurance. As far as interest rate goes, it definitely helps the insurers, because they invest a lot of the income, but it introduces volatility in the asset valuations. There’s climate change as we all know, there’s been the increased frequency and severity of cats, which causes uncertainty when doing cat models and things like that. So to keep up with that is very hard. The reinsurance market in general has been very hard. So there’s rising cost and tighter capacity. So following years of large cat losses, reinsurers have increased their prices, which can make it tough for insurers to place the reinsurance, in a lot of instances. There’s, as we know, regulatory pressures, all different types of solvency and capital requirements. There’s NAIC, RBC in the US, there’s Solvency II, there’s IFRS, and then there’s cyber and emerging risks that are coming around, it’s a whole new area, so it’s hard to price things. There’s data and technology issues, legacy systems availability to data, you know, poor incomplete data to do modeling and pricing and placement. And then for a reinsurer, there’s also the limited capacity for retrosession. Retrosession is when the reinsurer itself is then taking out additional reinsurance, spreading the risk further around. So lots of different topics when it comes to challenges for insurance companies and reinsurers.

Mark Sidlauskas: There were a couple of terms there that, maybe you could explain to me when you say cat, what does cat mean?

Craig Robinson: Oh I’m sorry. Yeah. Catastrophe losses. So things like hurricanes.

Mark Sidlauskas: And what is a hard market versus a soft market?

Craig Robinson: Hard market is just when reinsurers are charging higher rates to place the treaties. As I mentioned, the treaties are facultative certificates. So that all has to do with pricing. They can charge more on any given year for a reinsurance arrangement, unless the following year. So the market has been very hard lately over the last many years.

Mark Sidlauskas: Thanks. And my final question involves everyone’s favorite two letters these days, AI. So where do you see the role for AI and reinsurance going forward?

Craig Robinson: I talked a little bit about the cat modeling, which I think is an area that AI can enhance the models, you know, just by incorporating real-time things like satellite imagery, data, etc. There’s underwriting automation. So supporting dynamic data-driven underwriting decisions, pricing models, there would be things like claim management, loss estimations, faster estimation of losses. It’d be fraud detection also contract analysis. So NLP which is natural language processing, where AI might be able to extract key terms and information from the treaties, to give improved clarity or reduce ambiguity, but also from a perspective of, a system like ours, where you can have that information automatically populated within the terms and conditions of the contract. You know, other things that probably would help with competitive analysis, cyber risk, intelligence, things like that, that I can think of.

Mark Sidlauskas: Pretty broad at this point. Lots of different use cases out there for it.

Craig Robinson: Yes.

Mark Sidlauskas: So thanks, Craig. Thanks for giving us the basics of today’s reinsurance market, and also a glimpse of what’s happening in our future and the possibilities of AI. The sky’s the limit for AI, really, so we appreciate you coming back on the show to share your thoughts. To our listeners, as always, we love hearing from you. So if you have any comments or would like to follow us on social media, please reach out to us on our channels and don’t forget to subscribe to the podcast. We’ve got so much more coming, so stay tuned to our Sapiens Insurance 360 podcast. Bye for now!

The post The Need for Reinsurance appeared first on Sapiens.

And since we’re now officially halfway through 2025, it’s a great time to ask what’s next for AI-powered life insurance? That’s the topic of today’s episode, and with me to answer this important question is return guest Dror Katsav, founder and CEO of Atidot.

Dror, great to have you back on the show!

Dror Katzav: Thanks, Jennifer. Always happy to be here. Great to be back!

Jennifer Smith: Well, we have so much to talk about today, so let’s just jump in and get started. Dror, can you explain what we’re seeing now in AI, what advances we can expect in the future, and why should insurers care about it?

Dror Katzav: It’s a great question. AI has been around for many years now, but we are seeing a significant change that happened in the last couple of years, compared to what we’ve seen before. We always had Netflix help us find the next movie to watch, and Spotify help us find the next song to listen to. Google maps helped us find the best route to drive from point A to point B, so we’ve had AI in our day-to-day lives since the early 2000s. But what happened in the last few years is that we got to this tipping point where there’s enough computer power, there’s enough storage, and there is enough data that AI has turned into something that is a little bit more than that. And we’ve seen that with the adoption of ChatGPT, and the like with generating images and generating text and generating capability, new capabilities that AI can bring into the table. The turning from a technology that is hidden in everybody’s devices to something that everybody is using on a day-to-day basis, and very aware of using AI. And we’re at the point where this AI is already on par with the performance of a human being. So we’re already at a point where ChatGPT can write text that is almost as good as a content writer. And image generation tools generate images that look like, still like a first sketch, but look like a very good first sketch of, of the graphic designer. And the code generation produces a code that is not like a super sophisticated, system architect would have generated, but it’s pretty good already. So we’re at the point where the AI is actually producing content and producing recommendations that are as good as a human being. And I think now we’re entering into this new era that is going to be even more exciting with regards to AI and the use of data. And across our lives, and especially for insurance.

Jennifer Smith: I absolutely agree with you, Dror. It’s been really fascinating to see some of the things that have been going on. And I mean, I know my kids and myself, I’m starting to use it more and more on a regular basis. It’s really becoming more of the norm. So what do you think right now we’re seeing as challenges, particularly with insurance companies? And what kinds of opportunities do you think exist in the traditional agent-led insurance sales cycle? And some of the solutions that we maybe need to consider for the hurdles that we’re seeing insurance carriers go through?

Dror Katzav: So I think insurance companies for years have always been adopting new technologies to adjust to new models. In insurance companies, you used to be one of the first ones to bring in statistics and probability. And then, you know, computers and so on and so forth. And I think by adopting AI, we’re going to see a new wave of how insurance is being done, it’s going to be very different than what we’ve seen so far.

I don’t know exactly how it’s going to look like yet, but I think insurance companies have to be in the forefront, because the ones that would understand first how to use AI for their needs are going to be the winners here. And there’s definitely going to be winners and losers, especially when you think about the current journey, the current buying journey, the buying journey that starts from the kitchen table and, the paper apps and even some of the e-apps, we’re getting used to [an] experience that is very different from the ChatGPTs of the world, Gemini, etc., that, you know, continuing with the same approach would work and would work for a few years. But it’s going to be slowly decaying while other approaches would emerge. I don’t know if you ever tried asking ChatGPT on your life insurance situation and what policy they would recommend to you. It’s not good yet, but it’s already pretty remarkable on the AI’s ability to read an illustration, AI’s ability to talk you through some of the concepts like, the IOL, second guarantees. The text part of it is pretty good. The math is not there. But these tools, evolve so quickly that eventually we’ll find ourselves in a world where, people don’t necessarily go to websites, when they can go to those tools and go through them and people will start expecting these experiences, where things are more conversational and things are more interactive, and relying solely on that distribution partner to bring in the business, it is going to be, is going to be very hard. Not to mention that the agents themselves, also people that live in the world and get used to these new experiences and are also expecting for these experiences to be more smooth and efficient and automated and personalized for themselves, as you know, part of the ecosystem.

Jennifer Smith: Do you think, Dror,  going off script a little bit here, that there is an opportunity to take some baby steps there and, kind of start with trying to encourage the traditional agents to really work with AI and more normalize it that way, and then learn from that, so that we can start to look at that kind of robo-advisor concept?

Dror Katzav: I think so, we’ve seen two examples, in the last..I have two examples from this morning, from conversations we had with different carriers. The first one was with a carrier where, what we’re helping them to do is take the data, break it into finer, tighter segments. So instead of sending one piece of marketing to all of the policyholders, they’re now able to send personalized messages to cohorts of people. And because of that, they get much better engagement. And because of that, those people get messages that are more targeted to them and more personalized and more appropriate to what they’re looking for. So that’s one way to get around this. The other way is, and we’ve seen that with another carrier, we had this conversation where they were saying, you know, the executives in the company and the mid-level management, they keep running into all of these problems with managing internal efficiencies. But when they come and ask those questions, they keep seeing that, the AI has already identified this as a probable issue and flagged that, you know, in a report that they get on a weekly basis with potential issues that might emerge this week. So when the companies will get more adjusted and companies that do get more adjusted to using these predictive reports and using these predictive segments and AI-generated content and so on and so forth, to know what’s behind the curve, they would be way more efficient.

And it’s a great way to ease our way into this. If I know, for example, which agents might have an influx of policies in the next couple of weeks and which agents might have a lapse issue. And what could be a good way to overcome that? And so on and so forth. We could be providing better service to the agents or to the customers, or to the internal team, and through that, get them more comfortable with us, providing them [with] AI insights on a regular basis. And ease our way into this.

Jennifer Smith: Yeah, really good insight, Dror.  I think that’s very, relatable for a lot of the insurance carriers who are looking for ways to help to, you know, gain more traction, get more business, and ultimately reduce the protection gap that’s out there and cover more people more effectively and efficiently. And as you mentioned, it really does come down to the data and the data that the insurance companies have had for, you know, decades and decades. We’ve been so data rich, but so information poor, and they’ve struggled to use it effectively. How would you say Atidot’s approach can change the game to utilizing data and AI? How can it solve the issue of how to efficiently and effectively use the data?

Dror Katzav: So first let’s take a half-step back and talk about what’s our approach. Our approach has been to go industrywide. So we work with different carriers and we work with different carriersand we work with different product lines. So term-life, whole-life, universal life and MYGA and fixed index and so on and so forth. And across these areas. we’ve seen no more than 60 million policies. I think the number today stands on 55; [it] depends on when we release this podcast. And because of that, because seeing 55 million lives across different situations, what policy did you take when you took this policy? How frequently did you pay the premium? Did you have premium gaps? Did you have payment issues? Did you exercise the rider? Did you decide to take partial surrender? Did you decide to lapse? And so on and so forth. Our models are very effective in providing insights that the carriers would not be able to produce themselves. So we come in and we already have a good understanding to what data points we might need. So it’s not, give us everything. Obviously as a data company, it’s always give us everything, but what we know what we want and we know what we can get the most use out of. We are industry-specific, so we can avoid some of the privacy and security challenges around that. And then we’ll produce insights that are very accurate. And I think that’s the biggest piece here, because although insurance is very much about statistics when it comes to engagement, people are still very sensitive on being able to make decisions, reach out to people, or give people recommendations when it’s very much statistics based. So if I’m able to produce insights of who is likely to lapse, who is likely to purchase, who’s likely to be underwriting at the 20% hit rate, or that 90% hit rate, it’s a very different story. And although, you know, we’re dealing with a world where you know, everything about insurance is statistics, still being able to get to this 80, 90% hit rate benchmarks, enable companies to feel more comfortable to go and engage in this, on these activities.

Jennifer Smith: Then position Atidot’s AI tools to insurers who are saying, there’s no way I could do that. I’m on these old legacy policy admin systems. And it’s going to just take forever to get this approved. How would you approach that with those, all those companies that just don’t think they’re able to do it?

Dror Katzav: So that’s exactly the reason why we build partnerships. We deal only with insurance companies. And as you can imagine, the tech stack is a nice hybrid of super modern and also super antiquated. And the way we approach this is through partnerships like this one, where we come in and tell the company, you know what? What if you don’t need to think about where the data is and where the integration is and how the infrastructure works, leave it for us, Sapiens and Atidot, to figure that out, understand where the data is coming from, where it needs to go to, how the insights can get back into your workflow within the policy admin or the underwriting benchmark or, the underwriting workbench, or the e-app solution, or whatever that is. Leave it to us. We’ll figure it out. We’ll take the data, put it back in exactly where you need it, and don’t think about integration and all of these pieces. Obviously, it’s hard, but between the two tech companies, it’s a much easier solve than having the carrier be in the middle. And also for us, you know, we build it once and we can redo it, you know, multiple times rather than come in and figure out what the, what the situation is every time from the start.

Jennifer Smith: Absolutely, [it] certainly is good to have a good partnership and for integrations. I know we’re running short on time. But I’m just curious to know around some of the results that you’ve seen with the insurers who’ve used predictive analytics and AI in their workflows. Can you comment on any of those types of results?

Dror Katzav: Yeah, 100%. We’ve seen that companies that use that to drive point-of-sale recommendation increase their conversion rate at the top of the funnel by 30%, meaning that, the likelihood of a person to actually end up buying the policy and paying the first premium increases dramatically. Through the work we do with Sapiens on UnderwritingPro, we’re able to improve efficiency dramatically for the underwriters that are using the platform, because we identify where the bottlenecks would be and help the company drive people into the right places. So we address those bottlenecks and shorten the cycle times on app underwriting. On the enforce side, we help companies reduce dramatically their lapse rates, all the way up to [a] 60% retention rate by being able to identify who is lapsing, why they’re lapsing, when they’re lapsing, how to engage with them, with which content, and help them drive this opportunity to improve, improve efficiency. So across the board, there are great results on improving, improving efficiency, as well as generating new revenue either from driving retention or driving, new app or upselling cross-sell across the board.

Jennifer Smith: Thanks so much, Dror. We really appreciate you coming back on the show to share your thoughts. AI and innovation is just such a fascinating topic right now. And when you couple that with what it can do for life insurance carriers, well, we obviously could have a whole other podcast on this topic and continue on as I’m sure we will.

So you’ll just have to come back again for another episode in maybe six months or so to cover the latest developments and what’s going on with Atidot. To our listeners, as always, we love hearing from you. So if you have any comments or would like to follow us on social media, please reach out to us and our channels and don’t forget to subscribe to the podcast. We’ve got so much more coming, so stay tuned to our Sapiens Insurance 360 podcast. Bye for now!

The post The Next Phase of AI-Powered Life Insurance appeared first on Sapiens.

So it’s no surprise to anyone in insurance that legacy systems are a drag on an organization’s productivity. Data is scattered. Underwriters get buried in manual tasks. Product launches take far too long. Adjusters end up juggling more complex cases, rising claims volumes, and tighter timelines. And all the while, customer expectations keep rising and competitors are moving faster. It’s a lot, but there’s a shift happening.

More insurers are rethinking how they work using agile, AI-powered platforms to automate the grunt work, connect the dots, and move at the speed their customers expect. It’s not just about keeping up; it’s about building a smarter, more responsive business. So to discuss this revolutionary shift, I’m joined today by Gil Trotino, Director of Product Marketing for Cloud & Portfolio at Sapiens. Gil brings over 20 years of enterprise software experience and leads our insurance platform strategy, including market analysis, product roadmap, and future vision development. Gil was with us earlier this year to discuss Sapiens’ AI approach, and I’m so excited to have him back to dive deeper into what’s preventing insurers from achieving operational efficiency and how agile solutions, namely Sapiens, can help them overcome their most pressing challenges to lead the way in today’s competitive market.

Gil, welcome back!

Gil Trotino: Hi, great to be back, Caryn!

Caryn Warner: So okay, let’s start with insurers’ pain points. What are the biggest operational obstacles you’re seeing that prevent insurers from achieving the agility they need, particularly in underwriting and claims processing?

Gil Trotino: Great question! One of the biggest challenges insurers face is around fragmentation, fragmentation of systems, data and decision making. Underwriting and claims processes involve, as we know, a lot of manual handoffs, inconsistent rules, and siloed technologies which slow response time and limit scalability. At Sapiens’ we are addressing these issues in several ways with our insurance platform. One of the core ideas of our platform is what we call single source of truth, which means that we collect, consolidate, and normalize data across all core and peripheral systems, including policy, claims, billing, CRM, and many other external data sources. This enables a true, consistent 360-view, ensuring that everyone in the organization, from the agents and the brokers to the decision makers, all of them are working with the same up-to-date information. For example, if a customer calls with a question about a claim, the service rep can instantly see their entire history, including policy details, past claims, payments all in one place.

Now, another tool that we have is our no-code business logic engine, which is also embedded across our platform and is used to manage and automate business logic so businesses [and] business users can easily build and adjust decision rules such as coverage validation, fraud detection, or claim handling without waiting on IT teams. When these two solutions are combined together, then we see the magic. Then you can basically achieve true data-driven decision making. Maybe let’s explore one use case around claim management to illustrate this. For example, in the life insurance claims, our no-code decision engine automates the claim-handling process by combining business rules with AI and machine learning models. So when a beneficiary submits a claim, then engine verifies policy details, coverage status, and the required documents, also using, by the way, AI, then applies a machine learning risk score based on factors such as claim account, frequency of claims, and historical patterns. Straightforward, low-risk claims are approved automatically. What you know, how we call it, it is straight-through processing or STP, while claims with unusual patterns or missing information or fraud indicators are routed to the claim handler for manual intervention. So this approach, which is a true co-claim handling approach, streamlines the claim resolution, reduces manual workload, improves fraud detection, and ensures faster payouts for genuine claims. Finally, agility is also about faster time to market, which means the ability of the insurer to quickly launch new product pricing models or coverage types to meet emerging customer demands. Our modular platform enables us to design and deliver integrated, end-to-end business solutions that align with real-world insurance flows across underwriting, claims, policy billing, and beyond.

And because it’s also open, we can easily plug in third-party partners and complement and expand our own capabilities. Let’s take one example, a great example I think, is our recent SMEs small medium business solution. We built it to streamline small commercial insurance by combining our core systems capabilities with ecosystem partners, such as region for data enrichment. That way, agents can get pre-filled intelligent forms, and underwriters can make faster, smarter decisions all within one seamless flow. It really shows the power of building solutions around business needs, not just products.

Caryn Warner: Wow, that’s a lot for insurers to consider. Tell us, how are insurers able to scale and adapt quickly in the face of so many different challenges and options, to consider?

Gil Trotino: So insurers today face a lot of challenges that make agility very tough. Limited IT resources, unpredictable spikes in demand, complex regulatory requirements, and of course, the constant need to innovate. That’s why SaaS is such a game changer. Using a SaaS platform such as Sapiens’ insurance platform, insurers don’t have to worry anymore about managing infrastructure or scaling resources themselves. They get a very flexible cloud environment that adjusts automatically to their needs, so they only pay for what they use. Plus, with firm SLAs and built-in compliance and security, insurers can trust their systems will be reliable and up to date with evolving regulations. Most importantly, this lets insurers focus their time and energy on delivering business value rather than firefighting operational issues. Also, continuous smooth annual upgrades mean that always insurers have access to the latest innovations without disruption, helping them launch new products faster, enter new markets and handle busy seasons with ease.

Caryn Warner: So let me ask you this, and AI is something that I think you mentioned earlier, I know we talk about it all the time here. Can you walk us through how AI serves as the foundation of Sapiens platform and drives customer success?

Gil Trotino: Yeah, absolutely. First of all, Sapiens AI isn’t just another feature that we are adding on top of what we do. It’s more regarded as a, as a foundation layer built into the core of our platform. So AI is truly at the heart of the Sapiens insurance platform, powering every step of the insurance value chain, and serving all key personas from the agents and the brokers to customers and employers.

The capabilities fall into three major areas. The first one is our rule-based auto reasoning. We touched [on] this earlier, but it’s worth emphasizing again, I think. Our no-code decision automation engine empowers business teams to manage complex logic, whether this is underwriting risk rules or claim processing flows. They can do it without relying on IT. This accelerates changes, reduces errors, and increases agility.

The second element is the use of machine learning and predictive analytics. We’ve built around 30 machine learning models that enhance underwriting precision, predict customer behaviors like buying propensity or churn, and help insurers make smarter, data-driven decisions. The third component is the use of Gen AI and Copilot tools. We embed Gen AI across the platform, providing smart assistant for automatic classification, instruction, and summarization of documents, for example, and other tools that surface the right insights to inform decisions.

Caryn Warner: Well, it’s pretty clear that the deployment of AI is a game changer in so many ways. I know we’ve covered a lot of ground today. So for our final question, can you just tie everything together by explaining the key drivers behind the Sapiens SaaS solution when it comes to governance and centralized management and how it ensures consistency, compliance, and operational efficiency at scale?

Gil Trotino: Right, sure. So in today’s complex insurance environments, we know that strong governance is essential. And that’s exactly where Sapiens excels. Our SaaS platform, which I mentioned earlier, provides centralized management capabilities of critical functions such as user actions, security policies, system monitoring, and third-party integrations. This gives insurers full visibility and command over their entire ecosystem. Reducing risk and simplifying the compliance, and by combining comprehensive governance with seamless, centralized management, Sapiens empowers insurers to grow confidently while minimizing the complexity.

Caryn Warner: Wow. So that’s incredibly insightful, Gil! Thanks so much for your comprehensive explanation of what today’s insurers should be achieving from their systems in terms of operational efficiency and how Sapiens’ agile SaaS platform may help insurers better scale and succeed in an increasingly competitive landscape. Thank you so much for sharing your expertise. And to our listeners, thank you for joining us for our Season Four premiere. We have so much more exciting content planned, and as always, we’d love to hear from you. Connect with us on social media, share your feedback, and don’t forget to subscribe to the podcast so you never miss an exciting episode. Until next time, this is Sapiens Insurance 360. Thanks for listening.

The post Solving Insurance Challenges the Agile Way  appeared first on Sapiens.

Our topic for today is claims digitalization, which is rapidly shaping and reshaping the insurance industry, bringing new opportunities for operational efficiency and importantly, customer satisfaction. The digital shift is transforming insurance in so many ways, making processes more efficient and improving customer experience. But with these benefits come challenges, like integrating new technology and getting employees on board. Today’s podcast, “Driving Successful Claims Digitalization in Insurance,” explores how insurers can navigate these obstacles and make the most of digital claims transformation. And with me today to explore this topic in detail is Anupam Malhotra, Associate Director of Enterprise Sales at Whatfix. Insurance carriers use the Whatfix platform to onboard, train, and support employees as well as customers on their internal and customer-facing applications and portals. Anupam who has been with Whatfix for over four years, directs the sales strategy, tailored to address distinct challenges in the insurance industry. His passions include digital transformation and adoption, leveraging insurtech solutions, and pioneering innovative approaches such as digital adoption platforms to elevate customer experience and internal organizational efficiency.

Anupam, welcome!

Anupam Malhotra: Hey Amanda, thank you so much for that introduction! Really glad to be here today!

Amanda Ingram: That’s awesome. Anupam, and we’re pleased to have you here. So Anupam, let’s get started. Let’s begin with what issues are claims adjusters facing when they’re using new systems or migrating to a new version of an existing system?

Anupam Malhotra: Yah, I think there is so much widespread transformation going on across the insurance industry today. We have insurance customers which are migrating to new core systems. We have transformations in the cloud going on. And we have new technologies like GenAI coming in. Now, technology is being introduced at such a rapid pace across the industry today that adjusters are getting overwhelmed with how to do things a certain way. You know, something as simple as an FNOL, how do I do it? How do I start using my new system efficiently inside my company? Now, you know, maybe today, adjusters have been using a homegrown system. They have been using a legacy system, and in comes in the shiny new technology which they have never used before. That’s a big challenge for any adjuster. We know that carriers are expecting efficiency gains by these transformations, but if the adjusters and employees are struggling to use their applications efficiently, there are chances that those efficiency gains will only remain on paper, right? The biggest challenge that I feel an adjuster might be facing today is he or she needs to understand maybe 10+ different applications to process a claim. Obviously, I’m working as an adjuster on my core claims system. I may be using a document management system, I might be using a texting platform and so on and so forth. Now, with new systems getting introduced, adjusters can struggle in doing basic tasks, like completing an FNOL, making a payment. The traditional modes of training are now getting ineffective. So the biggest challenge that adjusters are facing is how do I get trained inside these new applications and new technologies? No one wants to go through huge pages of a PDF or watch a video to understand the system. And then there is no contextual help and support for the adjusters. They then end up making more errors while working on claims. Moreover, there is so much complexity that insurance brings in so many process compliances regulations that an adjuster needs to be aware of, and there is no easy way for an adjuster to get that information at their fingertips, right? Especially when I’m working on a new system. I need all the information I need. To make the claim process quickly without making too many errors. And that is precisely what is happening today with adjusters.

Amanda Ingram: It’s certainly challenging, isn’t it Anupam, when you’re faced with a brand new shiny, shiny system and you don’t quite know what to do with it?  It’s a fascinating topic and haven’t explored, you know, some of the challenges that you’ve already mentioned. Explain to me a little bit more around how digitalization is solving problems? And, you know, some of those problems that you’ve just outlined. When they’re using these new systems and particularly when they’re looking at the practical level of things, you know, how do I do certain things in this new system? Can you dive into a little bit more for us?

Anupam Malhotra: Sure. Amanda, I think that’s a really great question. Obviously at a high level, I feel digitalization is helping the industry tremendously. We are seeing efficiency gains happening because of digitalization. It’s making the customer experience better. The claim processing times are improving. And we are seeing numerous such benefits that digitalization is bringing at a higher level. But when we go deeper and look at the practical level, we also see that, you know, when the digitalization is introduced in the right way, an adjuster spends less time in searching for information, he or she is providing the right information contextually in the flow of work while processing a claim. Now that just not improves the adjuster’s efficiencies, but also improves the end-user experience. By end user, I mean the policyholder experience. And, you know, we all know that when a customer is filing a claim, the experience that the customer gets at the time of filing a claim will determine largely whether the customer stays with the insurance company or moves on to another company. And it’s extremely important to provide that right experience to the policyholder through digitalization. What is also happening is that because of digitalization happening across the industry, employees and insurance companies are becoming more agile in adopting new technologies, getting proficient, with these, you know, numerous technologies. The errors are getting reduced and new products are getting introduced more quickly. Right. So overall, I see a lot of productivity gains happening, because of the digitization that’s happening across the industry.

Amanda Ingram: It’s quite challenging, isn’t it? You know, I mean, certainly, you know, working in the insurance industry ourselves, the speed at which, insurers can launch new products to market now. And you know, the uses of the internal systems of the customers have to adapt to all of these new things very, very quickly. I really liked the way that you talked about, you know, contextual assistance and how we can help both internal and external users of the system. So let’s shift the conversation a little bit and explain to me how and to our users and our listeners, obviously, how Whatfix can empower users, such as claims adjusters and customer service representatives with those self-service capabilities that you’re mentioning to improve or improve the overall efficiency?

Anupam Malhotra: Sure. I think when I, when I want to explain [what] Whatfix does to somebody that I’m speaking with, for the first time about Whatfix, I always give this analogy, you know, think of Whatfix like a GPS for your application. It could be a core claims system, it could be an underwriting application. It could be an agency portal. But since Whatfix is application agnostic, you can have the same experience on any of these applications. But in the context of today’s discussion, which is focused on claims, think of Whatfix as an overlay that is sitting on top of your claims application and providing contextual help to your claims adjuster.

Now, the claims adjuster today need not FNOL and read a document to understand how do I do an FNOL inside the system? Instead, what he or she needs to do is log in to my claims application. And I will be guided in real time by Whatfix inside the application itself. Any help that I need as an adjuster, is provided to me inside my claim system. Now, what that ends up doing is solving multiple channel challenges for the adjuster. Number one, it helps me find the relevant information. I can do that very easily without having to spend too much time finding for that information. The right information is provided to the adjuster at the right time inside the application itself. Secondly, what it ends up doing is adjusters make fewer errors as Whatfix provides very contextual nudges and reminders to the user. Thirdly, we are also seeing improvements in process compliances, regulations, and all that improves as a result of it. Now, I want to give an example on this scenario wherein we had this particular insurance company where the claimants were supposed to provide a rental, in case of theft of an entire vehicle, but that was not happening.

So Whatfix started providing these smart nudges inside the claim system, reminding the adjuster to make sure that they’re providing a rental, to the claimant. And that started improving the adherence to this particular process tremendously, post-Whatfix implementation. The fourth benefit that we are also seeing is the change management is streamlined. Now the new changes now communicated, inside my system, instead of sending numerous emails which no adjuster is reading today. And finally, the last benefit is that adjusters get trained and onboarded quickly onto the system. They get proficient inside these applications very quickly. Now, think of all the contractual workforce that carriers hired today. To do, you know, process those volumes of claims coming in. We need a way to train my, contractual workforce quickly, efficiently, and get them productive so that they start processing those volumes coming in, in a timely way. So I think these are some of the benefits that Whatfix can bring in.

Amanda Ingram: Thank you, Anupam, you explained it very clearly, and I particularly like your analogy of a GPS system for claims. I really like that. I think that’s great. And the real-time guidance and compliance that you provide into to the users as well. And I particularly know what you call them, intelligent nudges. I really like that as well, because that tells me that the system knows when it needs to give a little push or a nudge to the end user. And that actually streamlines and again, improves that overall customer experience. So let’s go on to another question. Let’s have a look at what role does the customer satisfaction and agent stickiness play in motivating insurers to adopt digital plans processes? And how are those expectations evolving?

Anupam Malhotra: That, that’s a great question, Amanda. I think, today agents and policyholders are spoiled for choice. There are so many options available to me as a policyholder when I want to get a new insurance policy. And my decision to go for the company will depend on the digital experience that I get while filing a claim.Right? If I, as a carrier, am able to digitize the claims journey for the agent and the policyholder in a very effective way, I’m building a competitive differentiator for me as, as a company compared to my competitors. A smooth digital experience, which is easy, fast, and uncomplicated, can actually lead to a happier customer. And we all know if a customer is happy, they are more likely to renew a policy.And similarly, if I have an agent, that’s getting the quotes and time that that is able to, self-serve themselves, they’re getting faster turnaround times. They are definitely going to stick around with me as a carrier. So I think it’s inevitable that the experience that my agents and policyholders are getting will largely determine, whether they stick around or whether they are loyal to me or whether they move on to another company,right? So I think it’s extremely important to bring that digitization in the right way and ensure that my agents and policyholders are getting the best experience that they deserve.

Amanda Ingram: Thank you. I totally agree with what you’re saying. Now, you know, that whole experience, it’s not just about using the system, being able to do a particular role, but it’s actually about, you know, improving the experience for the customer at the end of it.I totally agree with you there. So we’re on our final question and could you please share with me some examples of some quantitative and measurable benefits that insurers are expecting to see after undergoing the whole claims digitalization process? You know, things such as, you know, reduce claims leakage or, you know, expediting the claims process, streamlining that claims process.

Anupam Malhotra: Oh, absolutely, Amanda. And then I think, at the end of it all, we all talk about digitization. But if you are not getting any tangible benefits out of it, what is the entire point of it? Right?

Amanda Ingram: 100%!

Anupam Malhotra: There have been numerous studies done recently, by analysts around this. And one survey, which I particularly remember is that, you know, it was by McKinsey and it mentioned that insurers who have implemented digital claims processes have seen up to a 30% reduction in claims leakage. And up to a 10 to 20% decrease in the claims processing times. Now, that’s a huge savings for any claims leader. When we look at it, some of the benefits that, you know, and another report back central came up with, talked about the fact that, you know, digitally enabled insurers have experienced up to 50% faster claims, settlement times, 40% increase in the in the customer retention rates. So I think overall, we are seeing so many benefits that insurance leaders are tracking today as a result of digitization. And with Whatfix, also, we have seen customers saving up to $1 million, just by, you know, being able to train and onboard that just as quickly and getting them proficient inside the application. So yeah, a lot of benefits. I mean, I can go on and on about this, but these are some of the ones I definitely wanted to highlight today.

Amanda Ingram: They’re great statistics, Anupam. They’re very impressive! I mean you know and any benefits and savings that the insurer is making, you know, whether that’s true, the claims leakage that 30% that you mentioned or whether, you know, it’s the million pounds of saving in processing and reduction times and all of these things, ultimately, that all benefits that the, you know, the insured, at the end of the day, whether they taken out the policy or whether they’re making the claim. I think it’s been a fascinating conversation. I really do thank you for joining the Sapiens podcast today, and for taking the time to appear here. And, and, you know, share your thoughts and you know, your insights with us. So thank you for that. As we said at the beginning with claims digitalization come startup issues, such as technology integrations, and polling, buying, etc. But with modern insurance applications, and no apologies for the shameless plug here, such as Sapiens leveraging Whatfix, to ensure minimal friction within the workforce. By doing this, insurers really can foster a culture that is ready for change and to remain competitive and in an evolving market. It’s been a fascinating session today, and I would like to say thank you again to Anupam, for joining us.

To our listeners, thank you so much for listening. It’s been really hard to believe that we’re already approaching Q2 of 2025. Where did those months go? But we have so much more exciting content and commentary in store. And of course, we love hearing from you. So if you have comments and you’d like to follow us on our social media, please reach out to us on our channels. And don’t forget to subscribe to the podcast! Stay tuned for our next episode of Sapiens Insurance 360. Bye for now and enjoy the rest of your day. Thank you!

The post Driving Successful Claims Digitalization in Insurance appeared first on Sapiens.

In the global, diverse world of insurance, Medical Professional Liability insurance may not be the first sector that comes to mind. But of course, that doesn’t mean that MPL insurance doesn’t have a long-standing history and significant market of its own. Also known as medical malpractice insurance, MPL insurance became more standardized in the early 20^th century as healthcare practices evolved. Heavy premium increases, tort reforms, including indemnity caps, and consolidation among insurers and healthcare providers have just been some of the highlights of the past 50 years. Today, the MPL industry continues to adapt to changing healthcare environments, legal frameworks, and medical practices, while diversifying in terms of risk management services, new coverage lines, mergers and acquisitions, and a lot more. With us today to speak to the MPL’s ongoing diversification journey is Bill Burns, who’s a Vice President of Research and Analytics at the MPL Association. Prior to joining the MPL Association, Bill also served as a Director on the Insurance Research team at Conning, where his main coverage areas were not only Medical Professional Liability, but also commercial auto reinsurance and general liability.

Bill, welcome to the program!

Bill Burns: Thank you, Jiffy! Happy to be here and I appreciate you having me on the show today!

Jiffy Thomas: Great, Bill. So let’s get started with you just giving us an overview of the MPL industry diversification efforts. Has the MPL industry tried to diversify in the past? Can you provide us some context and background color?

Bill Burns: Absolutely, Jiffy! So to answer this, I think it’s best if we go back and start at the beginning. So the MPL industry as we know it was created in the 1970s due to a crisis of availability. At the time, the commercial carriers dominated the market but were losing money because of rising frequency and rising claim severity. So they pulled out of the market and left a void where the insureds had no options. So the mutuals/bedpan companies were set up by medical and hospital societies to fill this void. But I think of these companies as special purpose vehicles that were largely designed to do one thing in one place. So if we fast forward about a decade to the mid-80s, we find ourselves with yet another crisis. But this one was a crisis of affordability and was again driven by rising frequency and severity. So at the time, the market found itself with loss ratios as high as 150%. And the only way to fix that problem is to raise prices. But then through a combination of factors such as tort reforms [and] improved patient safety, we saw underwriting results improve tremendously. Then, as icing on the cake, during the late-80s, the interest rate environment was very favorable to fixed-income investors. You had 10-year treasuries throwing off seven and a half to almost 10% at that time. So as a result of all this good news, the early ‘90s in particular, ‘91 to ’97, average operating results for this industry were about 67%, which meant that the industry was making $33 of pretax income for every $100 of premium. Well, policyholders surplus grew significantly, and companies found themselves with money to spend that they didn’t have before. So companies got to thinking, if we can do this in our home state, we should be able to make even more profit if we grow into other states and other sectors. So what you saw was, for example, the New Jersey doc company growing into Pennsylvania hospitals. You saw the Pennsylvania hospital company going into new Jersey docs and etc., etc. So it should be noted at this time the companies were also looking to get financial ratings. Many of them had no rating at the time. They were looking to get an ‘A’ rating potentially, which would allow them to diversify even more and not be 100% in their home markets.

Jiffy Thomas: Good, good. Thanks for that, Bill. So it sounds like, start small, start local, and then expand over to other states, right?

Bill Burns: Yes.

Jiffy Thomas: So, how do you think those diversification efforts have worked out, so far? And what have some of these companies learned from those experiences?

Bill Burns: Well, let’s keep it up until the hard market that we saw about 25 years ago. As I mentioned earlier, you saw a lot of companies diversify into markets where they had expertise, for example, doc company writing more doctors. You also had companies where they wanted to apply their MPL knowledge in other healthcare sectors. So doc company writing hospitals. However, the diversification we saw in the ‘90s was largely done on price. Why? Because the quickest way to burn into a market in insurance is to undercharge the competition. So that’s what companies did. They also tried going after better risks, for example, claim-free doctors, certain classes like anesthesia, etc., but the incumbent companies knew those risks. They knew their markets and they knew the defense attorneys. So in many cases, the risks that came to market were a lot of times bottom feeders. They weren’t the cream of the crop. So to your question on how this worked out, in a word, not so good. Industry combined ratio shot back up to the 140-150 range. Some companies took the diversification idea too far and found themselves priced out of business. Examples of that are PHICO, Frontier, a few others. Some companies just pulled out of the market, in particular, St. Paul, which was the largest writer of MPL at the time. Now for the surviving companies, a hard market set in and around 2001, which lasted for about five years. And we saw in some cases persistent year-over-year, double-digit price increases. This hard market, as I said, lasted until about 2006 when things settled down. So what were lessons learned? Well, one lesson is that it’s very easy to grow in insurance. All you have to do is underprice the marketplace. Another lesson is, profitability is a different story. So if companies insist on underpricing business, there will be a “road to Damascus” moment when they realize they can’t underprice forever. The third thing that came out of it is, I think the industry walked away more responsible about diversification and what that should look like.

Jiffy Thomas: Diversify, grow into other markets. But then there was a hot market that came into play, right? So other factors coming in. So just moving on after the dust settled on this last hot market, how has the industry looked to diversify its core operations to get some of those costs and loss ratios better?

Bill Burns: Well, things settle down. That’s the insurance industry. We have a crisis and then we move on. Our industry, what we saw post the hard market, companies continue to look to diversify. They just did it in a more responsible fashion. So you had companies that look to diversify in what they knew in other states, sometimes contiguous, sometimes across the country. But they went into the markets knowing more than they did, say, during the ‘90s, when they just jumped in the markets with both feet. There was a fair amount of M&A activity during that time. We had some companies like TDC, which made several purchases like SCPIE, FPIC, and now ProAssurance, which was the biggest news recently. ProAssurance was an acquirer of companies. I remember they bought the Podiatry Company about, probably 12 or 13 years ago. MAGMutual bought MD Advantage and West Virginia Mutual, so M&A activity is normal. That’s normal activity in any business. Some companies went into other lines of business. ProAssurance comes to mind, with the purchase of Eastern Alliance, which was a work comp, is a work comp specialty company. MAGMutual went into commercial auto to provide coverage for healthcare, auto risks. Then you have some companies going a little bit further. ISME has gotten big in the international space. Some companies are writing assumed reinsurance, they’re actually acting as full-blown reinsurers for healthcare writers. NCMIC and COPIC come to mind on that. And then you have some noninsurance areas. For example, Coverys got into the risk management and consulting as well as the education and training businesses and Curi is in the investment advisory business.

Jiffy Thomas: So, we went from companies vacating the markets to small mutual companies coming together, expanding. And then now you’re seeing a consolidation, mergers and acquisitions going on. Great! So, why are these companies looking to diversify today? What’s changing the, today’s environmental climate?

Bill Burns: There’s two big changes that have and are taking place, Jiffy. First, following the last hard market, one of the dynamics that truly benefited the industry was a drop in claim frequency. And we’re talking a drop of maybe 30, 40%, where the claims just went away. So at the time, the market was assuming prices that would cover a certain number of claims, but those claims didn’t appear. So the pricing in hindsight, was very overstated in some cases. What that led to was significant, favorable loss reserve development. And what that did was ultimately, it found its way into the policyholder surplus because the money wasn’t needed to pay claims. So between, say, 2006 and last year, 2024, policyholders surplus for this industry went up about 200%. So you have a number of MPL companies finding themselves sitting on large amounts of surplus and looking for ways to profitably deploy the money.

Jiffy Thomas: Uh huh!

Bill Burns: The second reason behind this, is that the whole picture of healthcare is changing. So about 10 years ago, physicians represented about 60% of the MPL market as we know it, in terms of written premium. Today, though, doctors only represent about 45% of the market. And this drop largely represents doctors that have gone from independent practice to becoming employees of hospitals or healthcare systems. If you think about Optum, which is a subsidiary of UnitedHealth, I believe they employ or work with one out of every 10 doctors in the country. So as a result, the doctor companies are looking for ways to grow, because the exposures just aren’t there in the doctor’s space.

Jiffy Thomas: Thanks, Bill. That’s, that’s an interesting dynamic trade here. You sitting on a bit of cash and premium, but the market’s shifting, people going more over to the hospitals. So for our last question here, what are some of the current paths MPL insurers should take in terms of diversification and what words of caution or encouragement would you put out there for MPL listeners?

Bill Burns: Well, we touched on a couple of them, Jiffy. International business assumed reinsurance and the tried-and-true method of expanding into other states, but cautiously, and with the right partners; don’t just jump in. There’s also a few other options I’d like to touch on that companies probably want to think about. And this message is largely directed at the mutuals, because by definition, the commercial companies in our space are already diversified. I think med malas a percentage of overall premium for commercial companies is maybe a 2%. So we’re talking here really about the mutuals that are largely in MPL. One thing they can think about doing is making structural changes. You might hear about companies setting up mutual holding companies, where the mutual company converts to a stock company, and the mutual holding company owns the stock, and now has access to capital markets. There’s also nonstructural changes, which could be affiliations or strategic partnerships, with other insurers that offer coverages needed by your MPL customers. work comp, cyber. It’s kind of a convenience, one-stop-shopping type of approach. Now, where we are seeing growth in this space is in the other facilities, the non-hospital, facilities, surgery centers, medi-spas where most care is delivered today. However, many of those risks are being written in the excess and surplus lines market. So if companies want to get into that other facility space, they should consider either setting up an excess and surplus line subsidiary or maybe partnering with an ENS company whose paper they can write up. Another interesting approach would be through an RRG. Now, RRGs have historically been used to insure a specific group of risks. For example, a group of docs that thought they might be better risks than their commercial or mutual company was charging for. So they set up an RRG to provide the insurance. Today, some companies are using RRGs as a growth vehicle, and this is because RRGs are less regulated than mutual companies and could have more flexibility in terms of pricing and coverage. And the last one I can think of is, is through program business. We hear talk about the MGA market and how that now exceeds over $100 billion in premium. And in order to write that business, the MGAs need partner companies. So many of these programs are written in the ENS market with a focus on property and GL. So it’s not med mal necessarily in play, but it is a way to diversify through other lines of business. So those are just some of the options that we can think of, Jiffy.

Jiffy Thomas: Thanks for your thoughts, Bill. I think we have just scratched the surface on the topic of the MPL diversification, much less where the MPL industry is going altogether. So hopefully we can have you again on the program to see what additional progress has been made. We’ll work on that! But in the meantime, thank you so much for appearing on today’s program and for sharing your valuable insights, Bill!

Bill Burns: Jiffy, the pleasure is mine. Thank you again for having me!

Jiffy Thomas: And to our listeners, as always, thank you so much for spending your time with us today. We love hearing from you, so if you have any comments or would like to follow us on social media, please reach out to us on our channels. And obviously don’t forget to subscribe to the podcast. We’ve got so much more coming, so stay tuned to our Sapiens Insurance 360 podcast. Bye now!

The post From Core to More: MPL’s Diversification Journey appeared first on Sapiens.

For me, one of the most rewarding parts of working in the insurtech industry is seeing how innovation isn’t happening in isolation. It’s not just about the breadth and depth of future-forward technology. It’s also about the partnerships across the industry that bring together expertise to create practical, data-driven solutions that today’s insurers need. And speaking of partnerships, with us today is our special guest Andrew Holdway, Head of Distribution Partnerships for EMEA at Swiss Re Reinsurance Solutions. Swiss Re is one of Sapiens’ many valuable partners, and a variety of Swiss Re’s risk data and risk insights solutions are out of the box and pre-integrated within Sapiens’ workflows, bringing together P&C risk information and market insights covering over 100 million SME and Mid-Market companies globally.

Andrew, welcome to the program!

Andrew Holdway: Happy to be here, Sally! Thanks for having me!

Sally Haines: Great. So let’s get started. First question might be an obvious one, but in a complex insurance market, what role do partnerships play in helping insurers modernize effectively? And on top of that, where have you seen the most impact when combining technology and data in a way that insurers can actually act on?

Andrew Holdway: Well, first of all, I think we should acknowledge that the word modernize will probably mean different things to different people, depending on what parts of the business they are sitting in. And secondly, I would hope that we all think of modernizing as a continuous, ongoing activity, not a one-off static deliverable. I’m sure we’ve all experienced delivering something that was thought to be modern at the start of the project, and fast-forward two to three years [and] it’s already looking outdated. And this really plays into the value of a partnership ecosystem that is a growing recognition that to build ourselves can be costly, timely, and possibly a distraction to other core priority topics. Therefore, we are really seeing clients reach out to that partnership ecosystem to help bring specialized and niche solutions that can fit within and around that core technology that can deliver impact across the value chain. And I’m not just talking about static print solutions or partner propositions that also continuously evolve to meet the increasingly demanding and evolving needs of policyholders, employees, intermediaries, and other stakeholders within the business. That is definitely a shift in how insurers see tech and data partners, lesser vendors, but a true business partner to lean into and support and challenge the insurers modernization journey. And where have I seen the most impact? Well, coming from an insurer in my previous life and now supporting multiple countries globally, clearly, we see tech and data as enablers to making better incremental decisions. And using underwriting and risk assessment as examples, we see huge impacts for an underwriter to consume and use data within existing business workflows that can reduce manual data entry, that can remove efforts from using multiple screens and sources to analyze, and then copy and paste data into code workflows, and move towards increasing straight-through processing, the standard of volume business, and to give the necessary risk insights for more complex business to support the underwriter to do what they do best: underwrite. And the output after is evident that’s risk-taking decisions more efficiently, a more healthy bottom line, happier employees to have the tools at their fingertips within existing workflows and not just providing data but really providing deeper insights.

Sally Haines: Great. Thank you. I think if we’re building on that kind of theme of evolving partnerships, insurers are constantly being pitched platforms, data sources, new technologies. What should they really be looking for in a partner that will help them to stay competitive in the next 5 to 10 years? And how can we make sure that we’re not just adding noise, but delivering clarity and insight for them?

Andrew Holdway: Yeah, good question. I mean, you go to any industry event these days, and it certainly can be overwhelming for insurers who enter a room with hundreds of tech and data providers, many of which with really great solutions. And you’re right to question this, how does an insurer sift through them all to find the right partners for today and also for the future?  With that start any relationship that needs to be a strong baseline, understanding what the needs and goals are, what is important to each other, being very clear and what can be delivered and by when? What is on the future roadmap, but also, crucially, what is out of scope completely? This has to be the basis of building long-term trust. The insurer must be confident that that partner can demonstrate a clear understanding of their business needs, and not sugarcoat any of their capabilities. Insurers should be assessing that partner for what they can deliver today, but also tomorrow. I mentioned earlier that insurers should be looking at their partners not as vendors, but [as] an extension to that core team that can be leaned upon, that can be proactive in bringing innovation, enhancements, new ideas, and also challenges to the insurance roadmap. And I’m not just talking about second data roadmaps, but insurers’ plans to enter new lines of business, new customer segments, and even new markets. For those on the other side of the table, we too want to contribute to that journey, and this can also be helpful for us as we understand the sense of direction that insurers are heading into and what capabilities we need to enhance or build to stay ahead of the curve and constantly provide impactful solutions. We see third-party management becoming a key governance, legal, and operational topic, too, with a preference and having less partners to ignore rather than having to manage many third-party providers. Therefore, insurers should also be asking themselves, what more can I corner do to support my business? Insurers may be surprised when we respond, but we should also be inquisitive to bring solutions proactively. And how do we make sure we’re not just adding noise? Well, really being crystal clear at the outset regarding business objectives and being able to measure success against these goals is critical. Being able to offer, for example, sandbox environments or POCs to test a proposition and gain feedback as to if the solution fits or not, and getting the shop a sense of the ROI. If the solution simply doesn’t fit, then it’s not going to be a long-term partnership anyway. But if a solution fits and it can demonstrate impact, then it could be the start of the long-term value creating partnership.

Sally Haines: Great, thank you. Lots to think about there. And I think if we are looking at it through the lens of underwriting specifically, we talk a lot about better, faster decisions. But what does that actually mean in the context of underwriting or portfolio management? And what does it take to turn raw data into trusted, usable input for decisions that carry real risk?

Andrew Holdway: Yeah, I touched on this slightly before, but ultimately, it means giving the underwriter or portfolio manager the tools with the relevant insights at the right time during a process embedded within existing workflows to make better risk selection decisions more efficiently. We hear many figures about how much time underwriters spend on non-underwriting activity, anywhere between 30 to 50% of the time, and the pain points for underwriters of needing to spend time outside of their core workflows to assess data and later bring the insights back into their core workflows, creating margin for human error and really the simple, monotonous task and time taken to do so. We also have pain points regarding the inconsistencies of what data underwriters use and when they use it, which then makes portfolio steering more tricky, too. Having consistency in terms of data quality, the data input stage, automated and enriching existing workflows, creates the output of better and faster decisions. Now, we have to be tough with pure raw data, as it could be difficult to see the forest for the trees, so to speak, and the same data set could be interpreted differently. Raw data requires deep analysis and a contextualized output depending on the use case. Your raw data on claims versus raw data on wildfire risk exposure. Once the raw data has been contextualized, it can be business ready for decision intelligence or usable info, as you called it. And this could be paired with, for example, underwriting business rules withinan underwriting workflow and trigger a next step or even a decision to accept ordecline the risk. We see challenges across the market with insurers not just having access to data but when they have it, not using it for all its power and insights. Therefore, this is a good question for insurers to ask themselves, do I have the right data contextualized in the right way for the specific use case? And am I leveraging the full insights it is providing?

Sally Haines: Great, thank you. I think we pivot slightly, but something that’s front of mind for a lot of people at the moment, is climate change and natural catastrophe exposures. They’re reshaping how insurers are thinking about risk. How do you see the role of external risk intelligence evolving in that space, and how do you think leading insurers can integrate that kind of insight into their daily decision-making workflows?

Andrew Holdway: Well, globally speaking, it is clear that the evolving frequency and severity of CAT events and those driven by the impacts of climate change are having a huge impact, not just on insurers and reinsurers, but the general population, businesses, and the public sector. As recent examples, we saw the flood event in Valencia last year that resulted in over 200 deaths, over 85,000 car claims, and over 35,000 proxy claims. We have the California wildfire earlier this year, and a devastating earthquake in Myanmar in March. Urbanization, growing populations, and underinvestment in defense systems and infrastructure, for example, also contribute to the vulnerability of communities and the resulting economic and insurer losses. Having better quality and easier accessible risk intelligence can only lead to more confident business decisions, and external risk data can contribute in a number of ways. For example, filling in gaps that the insurer currently does not have, providing more granular insights compared to what the insurer already has or versus what is publicly available, bringing in expert views on specific hazards and perils. For example, bringing in forward looking views, for example, the impacts on climate change, and more frequently, we see insurers using external data to provide a second opinion. On the prevention side, better quality risk intelligence is becoming ever more critical for insurers to be able to mitigate impacts of risk events. Be proactive with policyholders ahead of more predictable events, work with the public sector to build a stronger systemic approach to managing risk, and also allocate appropriate capital to pay future claims and remain within solvency ranges. On the risk selection side, having better quality decision intelligence enables insurers to select the right risks at the right price, on the right terms, but to also have such granular insights to be able to explain to stakeholders why certain decisions are being made. It creates transparency in the industry, which sometimes is lacking. And then on the portfolio management side, having better decision intelligence to steer allocation of capital, retained and reinsured risk levels and structures, scientifically drive go-to-marketstrategies, and have real-time impact analysis, for example, contributes to a healthier management of folios and the ability to be confident in decision making and communicating to stakeholders with conviction. And how will leading insurers integrate to this, this insight? Well, I mentioned a few times now the phrase “decision intelligence.” And this is exactly how leading insurers are integrating data at points of decision within workflows to support better and quicker decision making. We see risk data being consumed in underwriting workflows, portfolio management workflows, dynamic pricing and rating workflows, accumulation management workflows. But also to support enriching SOVs. Risk engineering, claims analysis, too.

Sally Haines: Great. Thank you. We’ve got time for one last question, and I’ve saved quite a big question for the end. But where do you think the biggest opportunities lie for technology and data to come together and really change the game for insurers?

Andrew Holdway: Well, in my view,second data can also be described as tools and insights. Insurers want to be able to use the best tools for user experience and operational efficiencies, and the most trusted insights to make better and faster business decisions. One without the other results in frustration, friction, inconsistencies, and also maintaining the chasm between tech and business teams. The biggest opportunity is clearly when the tools and insights act harmoniously together, with seamless user experience within common workflows across the value chain. But also with this, a continuous and data-driven automated feedback loop so that the tech teams can deliver as the business needs evolve and the business teams have a clearer conviction of their needs to communicate to the tech teams. We have a mutual client had a team sitting between the tech and business teams, and they orchestrated amazingly in marrying business needs and capabilities. And with one of the head of the underwriting business teams describing our combined underwriting solution as a dream come true.

Sally Haines: Right, I think a dream come true is probably a good point to end on. So thank you. I know there’s a lot more that we could talk about when it comes to the combination of partnerships, tech, and data. So I think the easiest solution is probably to have you back again for an encore and see what additional progress we’ve made in the months ahead. We’ll have to work on that. But in the meantime, thank you so much for appearing on today’s program and for sharing your insights.

Andrew Holdway: The pleasure is mine, Sally. Thank you!

Sally Haines: And to our listeners, as always, thank you for spending your time with us today. We love hearing from you. So if you have any comments, please do get in touch. And obviously don’t forget to subscribe and stay tuned to the Sapiens Insurance 360 podcast. We’ve got lots more to come. Bye for now!

The post Shaping the Future of Insurance: The Power of Partnerships, Data, and Technology appeared first on Sapiens.

Laurie, welcome to the show!

Laurie Von Dauber:Thanks, Chris. I’m really excited to be part of this conversation. Modernization is about more than new technology. It’s really about using technology the right way to drive real business results. In my role here at Sapiens, I work closely with carriers of all sizes, helping them shape their modernization roadmaps to deliver that faster, smarter service and stay competitive in a market that’s moving faster every day.And while trends like AI and digital are changing fast, it still all depends on the strength of the core. The better a policy billing and claims system is, I think the more effective digital data and automation efforts will be. So, Chris, with your background in claims transformation and with my focus on policy and billing, let’s share today what we’re seeing for how leading carriers are navigating this next phase of modernization.

Chris Daniels: Okay. So let’s get things started. We know carriers are modernizing to solve real business challenges in not just upgrading their technology. So, Laurie, when you’re talking with carriers, what are they really trying to accomplish with their tech investments?

Laurie Von Dauber:That’s a great question, Chris. So when I work with clients of all sizes and tiers, and they’re writing commercial, they’re writing specialty as well as personal lines. And when I respond to RFPs and I’m prepping for demos of Sapiens solutions, my focus is on what the carrier strategy is. So I’m always asking myself those questions. What’s driving their motivation? What are they aiming to solve and how can our solution help? So that my presentations, my response is in an RFP are focused on the business outcomes they want to achieve. And we’re seeing that focus reflected more broadly across the industry, too. So recent analysts surveys show that midsize P&C carriers, especially those midsize carriers, they’re stepping up their IT investments this year, really prioritizing modernization to drive those outcomes. I also see that importance of fast, automated turnaround time and decision handling, which requires data insights, risk assessment, as well as capacity, all achieved by an insurance platform like Sapiens, which delivers that end-to-end intelligent business solutions by integrating the core capabilities with data analytics and AI. And finally, as I think about this, insurers look to modernize their business to stay competitive with newer insurer tech companies entering the market. That’s where a SaaS solution allows a carrier to stay on top of advances in technology as they emerge. Cloud systems offer that greater agility, making it easier to deploy updates, launch new products, and respond to market changes. Sapiens has partnered with Microsoft to enhance capabilities and performance of insurance companies through cutting-edge technologies and cloud-based solutions.

Chris Daniels:All good points, Laurie. So when I think about modernization strategies, a lot of it is focused inward, as you’ve been talking about streamlining operations, improving decision making, gaining agility. But today, speed is the name of the game, right? And a lot of that pressure is coming from outside the organization. How do you think external entities are shaping how carriers think about modernization?

Laurie Von Dauber:Yeah, I’d agree that another key factor in modernization and growing up the business is that investment in technology for the improved customer engagement as well as the customer experience piece, right? Digital portals, they’re convenient, they’re personalized, and in some cases, they’re allowing the customers to quote, bind, and even manage those policies online. That’s all in turn, automating underwriting, shifting underwriters toward the more complex, value-driven cases that digital self-service, in fact, it has become one of the top capabilities carriers are prioritizing this year for 2025, according to some recent industry insights. And especially among those midsize insurers aiming to strengthen their customer loyalty.

Chris Daniels: Yeah, I completely agree. And I’ve seen firsthand, you know, how important the digital experience is, especially across the claims space. You know, someone dealing with a loss, they’re not thinking about systems. They just want a simple way to check on their claims status, to submit a document, maybe, or to send a quick message to their claim drop. And I think most people, if they’re like me they would rather do that in a matter of seconds than wait on hold for someone or to navigate a frustrating phone menu or a voice response system. Yeah, I think providing them that kind of access through a digital portal or a mobile app, it has a huge impact on satisfaction and trust. And that brings us to the next part of our conversation, okay? So if modernization is the why about what’s driving this, then core systems [are] the how. So Laurie, what are carriers today looking for exactly in a modern core system?

Laurie Von Dauber:Carriers are looking for flexibility. They’re looking for user experience and integration with emerging technologies. So according to the latest research, core system transformations remain a pivotal priority for P&C insurers. In fact, this investment is still making up about half of insurers’ IT budgets. So when I think about what carriers are looking for, what comes to mind is a strategic platform. A strategic platform offers a strong partner ecosystem which gives carriers access to plug and play of insurtech data providers. AI, and digital tools. The challenge they have today is a lack of that flexibility and support for emerging technologies like your GenAI, which offers the document summarization and the interaction the Q&A capability for faster insights. So a modern core system lets them pick and choose the right partners for their specific needs and their markets, all while staying within a common architecture, which is a real benefit there for keeping integration time and costs low.

Chris Daniels: You’re spot on. I spent most of my career, as you know, working on the carrier side. And honestly, you know, not that long ago, integrating a new vendor or service partner was a real challenge. It was a nightmare. We were so dependent on IT, time, and resources to hard code things. Things that today have really become seamless, more plug and play that you said earlier. You know, if we couldn’t get the work prioritized, we just had to ask our staff to log into another external system just to get the job done. It slowed everything down, created frustration across the board.

Laurie Von Dauber: Exactly. I think it’s still a real issue for a lot of carriers. And in fact, it reminds me of a recent engagement where the claims leadership was telling us that their teams were bouncing between nine different third-party systems just to handle daily work. So that’s why it’s not just about integration. It’s really about that smart connected workflow, as well as the ability to retrieve third-party data. That’s also really important. Core systems need to integrate with partners, allowing for ingestion of application and third-party data for that prefill during the quoting process. And then during the policy lifecycle itself, partner support things like servicing with the call center functionality or billing and payments, texting. All of that aids in productivity and efficiency.

Chris Daniels: Right. And you know, from a claims perspective, you know, we see something similar. Carriers are increasingly looking to use data not just on the back end, you know, after the fact for reporting, but they’re looking for real-time insights into workflows to support decision making, especially around predictive and prescriptive analytics. So, Laurie, we started getting deeper into the specific functions. And so let’s think about how carrier expectations play out differently across policy billing and claims. Laurie, can you walk us through what carriers are really looking for?

Laurie Von Dauber: Sure. So as the backbone of an insurance operation, a policy admin system needs to be robust, needs to be flexible. It needs to be efficient to handle large volumes of both policies and transactions on those companies. These it needs to be cloud ready for better scalability. Policies need to be issued timely for the profitability piece of it. And this is where the frameworks and tools to support underwriting really come into play. As we’ve been talking about today, that really helps automate risk assessment as well. And the underwriting decisions, the role of the underwriter is elevated to work on submissions where risk characteristics are outside of the risk appetite defined for the straight-through processing. I think a well-laid-out underwriter dashboard is really important, right? It needs to have those capabilities for notification for when the underwriter gets involved. And that leads us then to the supervisor manager visibility into tasks assigned and things like reporting on metrics for task completion time. From what I see, carriers are looking for that workflow management and the work distribution handling. And as I think about it, some other things that are coming to mind are communication. That’s an important piece, such as quote proposals that automatically will be e-mailed out to the agent. It’s really important for carriers to consider what workflows and policy transactions are also pre-built in the core system. Are out-of-sequence endorsements supported? What about audits? In a current client engagement that I’m working on, I see the need for digital channels for intake. Then as submissions are received, the underwriter needs to be notified from the underwriter dashboard. The underwriter wants to see their list of submissions. They want a means of prioritizing those to know what to work on first. And then with that being said, it’s important to track when those items are due via those dashboards to see that assigned work across teams.

Chris Daniels: So these things focus on the underwriters’ operational efficiency. How could the core system support a carrier’s growth into new markets?

Laurie Von Dauber: Yeah, when creating new products, it’s really important for the carrier to think about how fast it is to roll out a new, a new product or a new state for an existing product. Some common questions asked, do you integrate with ISO, how are state jurisdiction, specific rules handled and tracked? In each of the demos that I’m giving, I’m highlighting that ability to configure the different products. Carriers really need that flexibility to configure those customized products quickly to meet those market demands. Now, thinking about it also, you know, a policy system, it needs to integrate with third-party data sources like your credit scores and geolocation, but it also needs to seamlessly integrate with your billing and claims systems. Now, when I think about billing, which might not always get into the spotlight, but in P&C insurance, it’s really mission critical. It impacts cash flow, customer satisfaction, and the retention, as well as that operational efficiency.

Chris Daniels: Right. You know, billing is not glamorous, but it is where trust meets the bottom line.

Laurie Von Dauber: Exactly. And what’s most important in billing is flexibility and bill plans, integration with third-party payment processors and banking systems. For your CSRs, that real-time account visibility into balances and payment history to handle those customer inquiries efficiently, your batch processes and automation, things like automated dunning and collections. So a modern billing system isn’t just about collecting premiums, it’s about enabling trust, reducing friction, and then delivering cash flow.

Chris Daniels: I think your point about trust and reducing friction applies to just as much as claims. From a claimant or policyholder perspective, trust is built, or even lost, in those first few touchpoints. Things like real-time updates and tracking automated payment status. Those things go a long way into reducing the anxiety associated with filing a claim. It can really simplify the experience and help with claimants feeling control. And of course, for adjusters, it’s about streamlining how they prioritize their work, how they investigate and settle claims. And you know, above all, not about drowning them in manual steps and workarounds and having them work in disconnected tools. All of that connects back to the core system. And I think it’s a perfect transition for how we’re going to wrap our discussion today. AI. AI is everywhere right now, and it’s quickly becoming part of the conversation around core systems, not just as a bolt on, but really as a driver of how systems and platforms are being built and used. Laurie, spend a minute and tell us how AI is further enhancing modern P&C core systems and underwriting.

Laurie Von Dauber: AI is everywhere right now, and it’s one of the insurance industry’s favorite two letters. AI technology is transforming insurance with efficiency, data-driven decision making, and of course, an enhanced customer experience. In underwriting. further enhancements will accelerate that straight-through processing. It’s going to automate more and more underwriting and leverage the expertise and the experience of the underwriter. It’s also going to allow the carrier to offer highly tailored policies to the insured. Now, I met with an underwriter last week who had been with their company for nearly 40 years. So she has that deep, tacit knowledge. I see AI amplifying her 40 years of wisdom, not replacing it. So AI really becomes a tool. It’s not a substitute. For example, instead of manually reviewing hundreds of pages of documentation, AI can go ahead and do that presorting and highlighting risks that the underwriter can then evaluate the true significance of. So your underwriting jobs just got more strategic, focusing on those complex cases and building those client relationships with a lot less paperwork.

Chris Daniels: Right. You know the articles and blogs that I read, you know, are saying that nearly two thirds of the large P&C carriers are expanding their use of large language models, specifically around document summarization, the example you were sharing. A final thought on AI. And I’m here seeing and reading lots of discussion on this. And it’s really about how carriers are working to balance the AI-driven speed and efficiency and keeping human empathy at the center of the insurance transaction. And I think that’s probably a podcast for another day.

Laurie, thank you so much for joining me today and for sharing your insights. There’s clearly a lot to unpack when it comes to core system modernization and P&C.

Laurie Von Dauber: I know we really just scratched the surface today, but I do hope our listeners took something from our time together. Thanks so much for inviting me.

Chris Daniels: Absolutely. To everyone listening. Thanks for spending time with us. We always appreciate your feedback. So if you’ve got questions, comments, or topics you’d like to hear more about, don’t be shy. Reach out to us on social or through our website. And of course, don’t forget to subscribe! We have more great conversations coming your way right here on the Sapiens Insurance 360 podcast. Bye for now!

The post Making Sense of P&C System Modernization appeared first on Sapiens.

Have you ever wondered how recent catastrophic events, such as floods or fires, have affected the trust consumers have in insurance? I think we can all agree that trust is the cornerstone of insurance. Insurers have one main job or role in society. If an insured suffers a loss, damaged car, flooded house, stolen belongings, they expect you, the insurer, to pay out. Returning them to the position that they were in prior to suffering the loss. This is what customers pay for along with peace of mind.

And they trust that you, the insurer, will pay out when they file legitimate claims. Some call this relationship honest insurance. But what happens when insurers face a surge in claims and fraudsters start taking advantage of industry challenges to prey upon insurers and policyholders alike? To discuss this important and very timely subject, “Staying Ahead of Insurance Fraud in Times of Crisis,” with us today is Christian van Leeuwen, Chief Strategy Officer and Co-Founder of FRISS. FRISS is one of the leading insurtech SaaS vendors and the industry’s first provider of the trust automation platform that helps P&C insurers support their trustworthy customers but also prevent and detect fraud. As a Chief Strategy Officer, Christian’s responsible for driving growth and innovation through the insurance industry, using the first AI-powered trust automation platform. And with over 25 years [of] experience in the insurance market, Christian has developed a deep understanding of the challenges and opportunities insurers are facing in digitalization and preventing fraud. Christian, welcome to the program!

Christian van Leeuwen: Thanks so much, Dean. I’m really happy to be here!

Dean Richardson: Great. So let’s start, shall we? So, the immediate question: how can insurers proactively detect and stop fraud whilst maintaining a smooth claims process?

Christian van Leeuwen: Yeah. Just let me start by explaining, of course, that more than 90, 95% of the customers for insurance are genuine customers. You want to instantly trust those customers when they file a claim. And if we look at how can insurers then proactively, detect and prevent fraud during the claims processing, it’s all about automation. So making sure that in real time, at every event during that claims process, that claim gets evaluated, screened, any anomalies or outliers are detected, and that they raise an alert for the claims adjuster or the special investigator’s review. One other thing is, that’s really important that these real-time events are tied into the core system. So integrated into Sapiens, in the Idit suite, for instance. Therefore, it is fed back into the event that the user can make the decision at the point in time where it’s needed. And the other thing which [is] really vital in maintaining a smooth claims processing is also that it’s end-to-end supported. That means that whenever a claim gets to special investigation, it is investigated and they are able to prove it, that it’s fed back into the system, and that, that bad actor or that provider or whatever person or object was involved, that also gets flagged with another claim and the process immediately, proactively stops new fraud or another exposure for fraud happening and even out the underwriting side of it. So that is the end-to-end setup where in talking about proactively detecting and stopping, that is, really vital to do.

Dean Richardson: Thanks for that, Christian, and great to hear. 95% of customers are genuine, but can you explain how fraudsters are taking advantage of insurers who are under an ever-increasing pressure to process claims quickly?

Christian van Leeuwen: Yeah, and then of course, processing claims quickly is also what customers expect. So that pressure is full on. And even when there’s a catastrophe or like a flood or a fire, claims loads will spike and even more pressure is on, on the claims analyst to process it quickly. And whenever that happens, we typically see a surge of two types of fraud in there. So on the one hand side, it’s opportunistic fraud. And then the other side is organized crime. So if you look at opportunistic fraud, it’s more or less the insured that tries to use the event to, they may really have a claim, right? Or they may stage a claim that they also have a claim, but usually they have a claim and they want to get more money from the insurer. So they make up a lot of maybe valuable objects, expensive objects that have also got lost, stolen or damaged by the event and therefore that, that is sort of they blow it up. And on the organized crime, they typically pick up such an event as a, as a trigger to start going door by door and trying to get the insurer to also have them file a claim on their behalf. And they try to really use those the events to, to get more money and to work together on the, on these fraud cases and the insurers, they typically need to respond fast on these cat events. So they might lower that threshold to, to be able to process all the claims. And that’s where we can help the insurers either by lowering the threshold to having it not block their process, but really at the same time, keep on checking all of the actors and the providers and all of the fraud scenarios that might occur. So having them, having [a] really close look into those and making sure that none of these frauds actually do happen.

So that, that is a bit of the time sensitive in helping them process quickly, but at the same time, using automation and being able to show that nothing of these frauds actually do happen.

Dean Richardson: It’s really interesting, Christian. So to pivot slightly, can you provide some real-world examples of post-disaster fraud cases and what the impact is on an insurer’s bottom line?

Christian van Leeuwen: Yeah, these post-fraud cases. Often the big ones, they are the organized crime. Organized crime, they’re the providers, they work together and they go to the insurer. Then they often also work together with the insurers to stage these claims together. And then these organized fraud banks, for example, there has been a couple of years back, there was this Operation Rubicon that is, that’s also public knowledge. So it’s a, you can find it on the internet as well. It’s a, I believe, it’s about $1 million fraud thing. So we’re finding a claim adjuster firm that’s working together with a lot of insureds. And they, they just involve them in the scheme and they file a claim. Get money and not paying for fixing a claim or damage because that is not there, but they just use that money to get it off of the insurance company. And the insurer then gets the innovation done and the provider can do the work. And, and they also stick money in their own pockets, of course. And these fraud rings, they can go to, up to, I’ve seen fraud rings of up to 16,000,000 in one single forgery. Then there might even be bigger ones. Right. So these are really hitting the bottom line of insurers. Of course, still, the opportunistic fraud if you add these up. Right. This also talks about millions of dollars and euros that that are impacting the bottom line. And these two together. Yeah, it’s really makes sense to block it. But ultimately you can lower your premiums for the genuine customers. Right. That is all of the what the reasoning is behind this. And making sure that you don’t accept fraud.

Dean Richardson: Absolutely. So it’s, it’s a huge industry problem. So, Christian, so here’s a key, key question for all of our listeners. So why and how can insurers be proactive rather than reactive in their fraud strategies?

Christian van Leeuwen: And I think that was a very good question. And I think I want to break it down into two pieces like the why as you said. So why does it make sense to be proactive? Ultimately, the money’s gone, right? So if, if you file a claim and you have an STP process with nowadays, with an instant payment, it’s not uncommon in Insurance. So the money’s gone and you have to try to get the money back. Or if you detect it and you need to get your money back, you need to investigate that claim. A lot of effort is needed to investigate that. So it’s always better to try to prevent this than later trying to detect it and investigate, you have to prove it. You have to go to court. And, and the example of the fraud ring that I just mentioned, I believe that that took years to settle in court, right? So these are really cumbersome processes. It takes a lot of them. And I think even there, the insurers are more like the moving into where the banks also work. And so they really want to be proactive, blocked whenever there’s exposure to prevent more leakage of the money. In terms of how, well, how can it be proactive ties a bit back on what the what we said in the beginning, right? It’s all about thinking about this in real time, making sure that you are at the event indeed at the first note of loss. Check what with the data that you have available, what and external data bring that in the mix, post it to our models, making sure that you find this relationship in our network in real time. And then look at that point in time, making sure that [it is] end-to-end connected, so that you can also use that at underwriting to prevent these bad actors from coming into your book of business. And there we see insurers more moving to an intelligence center where also intelligence with police and other industry fraud bureaus or the national fraud bureaus are shared. You also want to load this into, your environment to be able to check if you have exposures with these, these bad actors, or maybe fake shell companies that are going around in setting up fake policies and finding claims on those. So these are, these are the things that we see happening where insurers are becoming more proactive and need to be more proactive, because these things happen across all the channels, the broker channels, the online channels, of course, all lines of business. So fraudsters do not distinguish between those things. They’re just simply out for the money.

Dean Richardson: Yeah, but Christian great to hear that you you’re stopping or identifying and stopping fraud not only at the point of claim, but at the point of underwriting as well. So, you know, as you say, stopping those bad actors, coming through the front door as well. Okay. So, Christian, just to wrap things up, I know there’s a lot going on with deep fakes at the moment, and especially with the recent new ChatGPT version. So what’s your advice to insurers on how to deal with this threat?

Christian van Leeuwen: Yes, absolutely. The thing explodes right now right in the ChatGPT since the launch [I] get a lot of requests, am I dealing with the deep fake? How do I know and what’s happened here? So to start off, I think we need to distinguish between two things. We have what we call shallow fakes, and we have deep fakes and shallow fakes, [are] more or less an image or a picture of your living room where people have planted expensive objects in there, to also make sure that they can file that under the insurance. So it’s an existing damage, an existing living room, and therefore, they add these things to it and it’s full, deep fake is for instance, a, an invoice. A fake invoice is completely fake, never been issued by a company. And the first thing to do actually is to start checking these deep fakes that are in the photo, and we even have that as part of the SwissRe platform to check for deep fakes and to get in this protection set up in in your process. Because you don’t know currently as an insurer if you, how big this problem is for you. So you really need to start there. And from that deep fake, deep fake checks, also start getting the data from the invoices and making sure that you double check what’s in there. So a three, full 360 check needs to be done on that. So that provider on there, is that a real provider? Is it actually located at that address? Those are vital things to start doing. The second is to really control your own communication. So that’s my advice to most insurers here as well, because deep fakes are there. It’s so rapidly changing that, and we are, we are keeping up right with that. But the new, we don’t know like what in like six months is possible with this technology a lot can be possible. So the second is to control your own communication, to make sure that you control how customers are sending in documents, how customers are sending in images. You want to verify that it’s your customer that sends in these images. So a lot is possible there as well, and I would just simply advise those two things to, for insurers to start looking into and setting up these basic checks. I know it’s a full podcast and so on, and I know we’re out of time, so I do want to like advise everybody, if you want to know more, reach out to Sapiens or to FRISS, and we can help you set this up.

Dean Richardson: Christian, thank you so much for your thoughts today and appearing on this show. I’ve learned something new. The difference between shallow fake and deep fakes. Thank you for that. Yeah, unfortunately, natural disasters and fraud are inevitable in today’s world. But savvy insurers with advanced insurertech can stay one step ahead of the bad guys or the bad actors as you say. To our listeners, as always, we love hearing from you,so if you have any comments or would like to follow us on social media, please do reach out to us across the various channels. And as always, don’t forget to subscribe to our podcast. We’ve got so much more coming, so stay tuned for our next edition of Sapiens Insurance 360 podcast and goodbye for now!

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And joining us today to discuss IBM’s Z next system is none other than Rosalind Radcliffe, CTO of the IBM Z and Linux ONE ecosystem organizations. Rosalind is responsible for driving the technical vision and product strategy for the support of the ecosystem for both communities. She’s also a select speaker at Industry conferences, a member of the IBM Academy of Technology Leadership team, and author of Enterprise Bug Busting, which explains how today’s enterprises need to examine how to achieve high quality with their software development practices.

Rosalind, welcome to today’s program!

Rosalind Radcliffe: Thank you, Tal! Thank you so much for having me on the show!

Tal Sharon: So, Rosalind, we have so much to discuss! But before we get into the technology aspect of the program, why don’t you first tell us how you began your journey and career in tech and how that journey led you to IBM Z?

Rosalind Radcliffe: Thank you. I’ve been in the industry for 37+ years, and I was lucky enough out of college to start with IBM in the ISPF organization, though I didn’t know a lot about mainframes at the time, I quickly learned, because ISPF is fundamental to the platform, and over my time with IBM, I have spent time in all sorts of different parts working with clients in our services organization, working in our sales organization, and working with worldwide requirements. I’ve spent a lot of time with systems management solutions, and had the opportunity to work across all of the platforms and solve client problems. And so Z has been at the core of that much of the time. And Z and distributed working together. And so it’s, it’s been a lot of fun and a great opportunity for me to learn and continuously grow in the technology field.

Tal Sharon: Thanks, Rosalind. Technology careers often have fascinating origin stories, and yours is fascinating and is a role model, especially since we just celebrated International Women’s Day. So moving on, can you first explain how mainframes help scale AI solutions for large organizations?

Rosalind Radcliffe: Yeah, this is a really important factor for the mainframe. It has been designed from the beginning and from the core up to support large transaction processing, guaranteed reliability, always on kinds of systems. It is from the core, the chip and firmware through operating system, making sure that our system is designed to allow you to scale up when you need to. And so it can handle those Black Fridays or there was a large insurance sign-ups or whatever it is that hits the system. It is specifically designed to allow you to do that, and that’s with all of the processing that’s been done within the system to make it easy for clients to run their system with eight nines and eight nines of availability, the scale of Black Friday.

Tal Sharon: Thanks, Rosalind. Now, with regard to the IBM Z next system, can you walk us through its key features, in particular its AI capabilities, given the growing importance and popularity of AI today?

Rosalind Radcliffe: Yes, it’s absolutely amazing! Every time a new generation of the Z comes out, there is a focus on continued reliability, sustainability, and the capabilities that we expect in the system. Every generation improves the way that we work with energy consumption to ensure it meets sustainability goals. With the latest discussions, we have the Telum II and the Spyre chip, and both of these have been enhanced for additional capabilities for AI. The Telum II has an updated IO processing that allows even faster access to data, which the machine was already built to for high IO, and this increases the access purposefully, because of the amounts of data needed in AI, and the Tellum II has the updated AIU. So the specific processor for AI technology, so you can run machine learning, you can run traditional AI processes in line in your existing applications. And the Spyre, coming alongside of that, allows you to run those large language models to do the additional inferencing that we want to do today. So with this combination, we can do an ensemble AI, allowing all of the transactions to process through the standard AIU, understanding whether or not it’s fraud or not, in a fraud example. And if it can’t really completely determine it, it could be passed on to the large language model for additional checks. So we really have in the next generation Z, a large focus on ensuring it can satisfy the needs for AI today.

Tal Sharon: Thanks, Rosalind. So for my last question, if there [is] one key takeaway about the impact of IBM’s Z technology on your customers or end users that you hope our audience remembers after today’s session, what would it be?

Rosalind Radcliffe: When I think about the mainframe and IBM Z and LinuxONE, think about it as a big server, a very large environment that can scale up for your needs are always consistent data and it’s not so different. It runs Linux, it runs OpenShift. You can take your existing capability and run it on the Z platform, as a full part of your hybrid cloud to meet sustainability goals of today. Being able to do AI processing on a custom system designed at its core to be able to do this processing, instead of necessarily for this using a GPU, use GPUs for what their needs need it for. Look at the processor itself. Look at the chip, and understand that we have different systems built for different uses, and look at IBM Z as that scale-up, available consistent data platform and use it for that and work with, in the hybrid cloud, the full spectrum of system.

Tal Sharon: Thanks so much for your many insights today, Rosalind! IBM is a giant in the world of high tech, and the IBM Z next technology is just the latest in its long line of innovations. I can’t wait to see how it impacts the insurance space, and technology overall in the weeks and months to come! And it was a pleasure having you today – your own career path was so inspiring and we at Sapiens are incredibly lucky to have you and IBM as a partner.

To our listeners, as always, we love hearing from you, so if you have any comments or would like to follow us on social media, please reach out to us and our channels. And don’t forget to subscribe to the podcast. We’ve got so much more coming, so stay tuned to our Sapiens Insurance 360 podcast. Goodbye for today!

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Stuart Hayman: Thanks, Laura. Happy to be back!

Laura Murray: Great. So let’s get started. There seems to be much more awareness now for the need for financial protection and resiliency. What do you think has prompted this?

Stuart Hayman: I don’t think it’s any one thing at all. I think it’s a combination of factors. And if we think back to Covid, that really focused people’s minds on the need for financial resilience and income protection comes to mind straightaway because throughout Covid, and thereafter, we’ve seen income protection education across the media. And this has been aided by industry efforts to communicate the benefits. And in addition, there are so many today, people in rented accommodation, and they too realize during COVID that they need an income to pay the rent in the event of being unable to earn an income through sickness or disability. And furthermore, regulation means income protection is now part of the holistic financial considerations for IFAs. So when you are sitting in front of an IFA now, as a customer, you can expect them to discuss your resilience in times of disability or injury preventing you from earning an income.

Laura Murray: Thanks for that, Stuart. So why do you feel we are witnessing an increase in income protection sales right now?

Stuart Hayman: Okay. I think it’s human nature, a lot of it. I think a cost of living environment really does focus attention on the importance of having a regular income. And with the increased awareness prompted through things like the pandemic, as I’ve already said, and particularly those without generous employer income guarantees, people have don’t mind looking at income protection as a security blanket. And the other reason is awareness. There’s been a plethora of education on income protection, along with real life case studies, and a lot of product innovation has really heightened the importance of this product. There is an organization called the Income Protection Task Force, a not-for-profit group based in the UK that was inaugurated back in 2005 with the aim of boosting awareness and as a consequence, boosting sales of income protection. And they’ve done this really, really well using real-life example case studies. It’s funded by the members from the personal protection industry, and Sapiens is one of those people. They also facilitate industry collaboration and provide resources for advisors to learn about and discuss income protection measures. And more recently, they have reached out to government to see whether there is a possibility to collaborate, particularly bearing in mind that governments are not just in the UK, but governments around the world are reviewing, their supply of welfare services.

Laura Murray: That’s really interesting, Stuart, and good to see that organizations are taking this on in quite a serious regard. Have the reasons for wanting income protection changed? As we know, traditionally these types of policies were written to normal retirement age to safeguard the policyholder in the event of disability or sickness.

Stuart Hayman: Yes, they have. Yeah. And it takes me back a number of years in my career in Life and Pensions, when income protection was a product written to retirement age, with the intention of providing an income in the event of disability or sickness throughout one’s working life. But now it’s not just regarded as a product just for income protection. And as I mentioned earlier, we’re seeing a lot more demand for this product from people who have regular outgoing expenses. And some people have marketed income protection as expense protection as well. And renters, again, are a very good point to consider, because they are very vulnerable in the event of disability or sickness from losing the roof over their head if they cannot afford the ongoing rent that’s due. And of course, with the cost of living continuing to rise, be that rent, be that food, be that utilities, be that whatever, having a guarantee of expense coverage, as well as income coverage, is becoming more and more essential.

Laura Murray: Thanks for that, Stuart. So there’s clearly demand, but how do you see insurers reacting to the current market?

Stuart Hayman: Well, the insurers are really, really the bull by its horns in this space. So what we’re seeing now are new income protection products with shorter terms and possibly even shorter claim periods to meet the different needs of customers. And one thing I’ve noticed particularly is that they’re starting to use data to target customer segments. And I come back to renters again, that’s a brilliant example of how renters are now a significant group who are looking for security. The self-employed, they’re another cohort particularly realizing the benefits of income protection and all this is being crystallised by economic circumstances. And what I mean by that is there is less reliance on the state and the cost of living, of course, and inflation. Added to that, what we’re seeing is providers provide what we call “added-value services.” And some evidence recently I was reading, is showing that these are really, really being taken up by policyholders. So things like access to doctors and specialists, services as a value add, access to a remote GP as a value add, access to mental health and physiotherapy services as a value add, access to lifestyle guidance, even second medical opinions. And with income protection, let’s not forget rehabilitation services. These are increasingly popular and insurance companies, yes, yes, they insure against risk, but they’re moving more and more and more to what I would call risk mitigation. And one of the new services is what I have read about is early intervention services. This is a service which allows those who suffer at a disability or an illness, resulting in a claim to get access to specialists to help them on their road to recovery.

Laura Murray: Thanks Stuart. So to wrap things up, do you think insurers will take advantage of the current economic uncertainty and devise other instruments to provide additional security? And since AI is topping on everybody’s radar at the moment, do you think AI will come into play with these new products?

Stuart Hayman: Most definitely. I believe we will see much, much more innovation in this space. And with an increased usage of data, I believe we will see providers developing very personalized offerings to their clients. And with regulation providers, as I said before, now have a duty to ensure the products and services meet those ever-changing needs of customers. Not forgetting that in this industry, we work in Life and Pensions, policyholders typically take out policies for a number of years and over that period of time, their needs change and the economic climate will change. And so, product providers have to be cognizant of that need and be agile and fleet of foot. And another thing I’ve noticed is that there’s much more attention on customer behaviours throughout their lifestyle. So we’re seeing behavioural management services coming to the fore as well.

Laura Murray: Stuart, thanks so much for your thoughts today and for appearing on the program. Today’s economic instability is a continuing story and we’ll all just have to wait and see how it plays out. But having insurance options that consumers can rely on to weather the stormy economic sea certainly provides peace of mind for so many of us. To our listeners, as always, we love hearing from you. So if you have any comments or would like to follow us on social media, please reach out to us on our channels. And as always, don’t forget to subscribe to the podcast. We’ve got so much more coming. So stay tuned for our Sapiens Insurance 360 podcast. Bye for now!

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Let’s talk about a problematic but potentially avoidable issue in insurance: fraud, specifically, soft fraud. What it is, why it’s often discovered in P&C and Life and Annuity lines of insurance, and most importantly, how can insurers detect it and prevent it? Here today to answer these questions and more about soft fraud is Woody Klemmer, Head of Growth for ForMotiv. ForMotiv is a Sapiens partner and behavioral science platform that helps insurance carriers predict user intent by analyzing digital body language while users engage with digital forms and applications.

Woody, welcome back to the show! You were here a little bit earlier in the season. And here we are, now already in the spring of 2025. Time flies!

Woody Klemmer: It sure does. Thank you for having me back, I appreciate it.

Jason Kozlowski: Absolutely. So, Woody, for our listeners, could you maybe define the current soft fraud problem that we’ve been talking about and maybe kind of discuss how it differs from hard fraud? And what makes it difficult to detect?

Woody Klemmer: Yeah. No problem. So just to level set and it’s, you know, we talk a lot about soft fraud. It’s a term that we’ve, for lack of a better term, stolen from other industry members, because fraud in general is just so broad. So many things fall under fraud.

And what we’re doing at ForMotiv, isn’t looking at fraud rings and life insurance, things like coercion or scam. So, you know, really hard-core fraud, the things that we’re looking at and why we think soft fraud is so interesting and important is and where we sort of draw the line in and differentiate is, is the hard fraud is more so, there’s no genuine intent. And with soft fraud, what we mean by that really is, when somebody is trying to get a policy, whether it’s, you know, an auto policy or a home policy or a life policy, they’re genuine about getting the policy. They’re just not genuine about their responses in order to get it. So, you know, take, again, life insurance, for example, when people are filling out a life insurance application and they get to some of the harder, you know, higher impact questions around smoking or alcohol or, you know, how much they weigh, if there’s been any weight fluctuations. What we’ve seen and what we’re really looking at is, is how truthful are people being when they’re answering those questions. It’s the same thing in auto insurance. You know, how many miles do you drive a year? Where are you garaging your car? You know, do you live in the city like I did? And maybe your address for insurance is at your parents’ house in the driveway because the premiums are going to be a little bit cheaper. Or how many drivers are on the policy, things like that.

Jason Kozlowski: Right.

Woody Klemmer: So when we’re looking at, again, the difference between the hard fraud and the soft fraud, we are very focused on the soft front portion. And it’s just becoming an increasing, increasingly costly problem for carriers today.

Jason Kozlowski: Gotcha. Yeah. That’s interesting. You know, you talked a lot about, the difference between soft fraud and hard fraud. What are you seeing is the real kind of financial impact that soft fraud is having on insurers and policyholders? Are there, as a result of that, are there better ways of detecting that soft fraud? You know, using some of the more advanced technologies that have maybe kind of come into place in the more recent years?

Woody Klemmer: Yeah. So I’ll, I’ll try to answer those in pieces. So, kind of starting at the beginning, yeah, the financial impact is enormous. Tens of billions of dollars, it doesn’t matter what line of business you’re talking about, if it’s auto insurance or home or life, whatever it is, it’s we’re talking tens and tens of billions of dollars. I believe the problem has gotten significantly worse because of the digital transformation. So it’s sort of the counter effect to everybody moving online. Covid obviously accelerated that. But when you have this whole digital distribution, you are no longer face to face with somebody. And I, you know, when you are face to face and it’s just it’s a fact, it is easier to lie, for lack of a better term, when you are behind a computer screen, when it’s just you and the computer. People are much more prone to misrepresent themselves, and the problem has only gotten worse. So the trends are terrible. I was recently speaking at a fraud conference. We talked a lot about the demographics, and because one of the questions from the audience was do you think this problem is getting better or worse? And the answer, unfortunately, is worse when you’re looking at younger demographics. The statistics there are pretty staggering. So we asked this question, and we read this survey that Verisk had done and it was do you think insurance fraud is a crime? And if you’re 55 and older, less than 5% said no. If you are 18 to 44, so call it the Millennials, over 30% said no. So basically 1 in 3 people do not think that insurance fraud is a crime. Well, you know, again, 44 or younger. And they asked another question, this is just another slide that we had around, are you using deceptive tactics to lower your premium? 40% of Millennials said yes. 3% of baby boomers said yes. So you’re seeing this hockey stick curve up until the right as far as, how likely it is that the younger demographics are going to be manipulating their policies to try to get a better rate. And there’s a lot of reasons why we could get into that. I won’t, because I know we’ve we don’t have a ton of time here, but that is creating a massive problem. It’s getting worse every single year. And carriers are looking for new ways to try to combat and fight back. You know, the digital policies. The toothpaste is out of the bottle. There’s no way they’re going to go back to just selling purely face to face and an agent distribution. And one of the ways that carriers are starting to push back and figure out how they can fight back against this is with companies like us. So, what we’re doing is looking at how people actually physically fill out their digital applications, we call it digital body language. But essentially, how does the user actually, how do they type? Where are they hesitating? Are they saying, yes, I’m a smoker and then going back and saying, okay, I smoke 10 cigarettes and then maybe five cigarettes, and then, you know what, forget it, I’m not a smoker. Smokers amnesia. We’re tracking that digital behavior and feeding it to carriers so that they can make better underwriting decisions. They can make decisions in real time. They can do it based on the individual. So as opposed to how they traditionally do it, which is, you know, post-issue audits or random holdouts, what we’re doing is looking at it in the actual application and underwriting flow, [in] real time, and then giving them the ability to triage those applications. And, you know, obviously, I’m sure you’ll have a little bit to say here too, given this is what we’re doing with you guys.

Jason Kozlowski: Right, absolutely. And you know, what you said is kind of spot on. And it’s what we’ve seen within the industry as well, working with our carrier customers. You know, it’s kind of really eye-opening what you said about the surveys and getting the different responses based on different age brackets. And, of course, as carriers start to move more and more toward that direct-to-consumer, kind of slowly but surely, especially on the life side, carriers are starting to make that, that shift more and more over time. And they have to appeal to that younger demographic who doesn’t necessarily, you know, isn’t used to purchasing things in a face-to-face environment, right? So I think that that’s really where we’re starting to see a lot of the focus, too. With our carrier customers is, how do we, determine any of that kind of, fraud or misrepresentation? And that’s been a kind of big shift over the last few years. And carriers are kind of desperate to get any of the information that they have available to them, to kind of help, assess, all the different ways that fraud might represent itself from anything from a nondisclosure to other information that, you know, there’s, of course, a lot of gray areas and a lot of different evidence, types and whatnot that come into play. And, during the underwriting process and, I think the kind of carriers, if they started to maybe shift a little bit, the pendulum maybe at one point went a little bit too far in the one direction where they were kind of starting to shift away from the way that they were doing business to, now it’s kind of shifting a little bit back. And they’re finding that happy balance of looking at and having all the information that’s available to them, and, and taking it all into account.  And absolutely, as you said, I think, what you’re doing at ForMotiv is fantastic, is really cool. And, and there’s a lot of carriers that are, that we’ve talked to in, in the last year or so, that are really interested in, just having that is another piece of the puzzle, right? In some instances, I think where, a good example would be we’ve had carriers that it was maybe a low face amount case, lower-risk case, and they didn’t need a paramedical exam, based on their agent amount requirements. But when you have the ability to flag something that’s potentially fraud, not necessarily, but based on their behaviors during the application, as you said, that may trigger the additional requirements that might need to be ordered, such as a paramedical exam and blood work to do that deeper dive to determine, is there, is there potentially some non-disclosure here, or did they legitimately, you know, click the wrong button during the application process and then correct their answer?

Woody Klemmer: Yeah. I totally agree. And you know, one thing I was just thinking about is you’re thinking click the wrong button. And things like that is, is I think, you know, we’re giving as an industry the customers a lot of grace. And you know, we’ve heard from carriers, you know, we trust the customers or we trust the agents. And you know, we do, too. I just think it’s a trust but verify-type situation. Another crazy stat I just thought of is, it’s nearly 50% of smokers don’t disclose it during an on-line application. That’s doubled in the last five years, a quarter, you know, almost a quarter of people don’t disclose how much they drank. They lie about their BMI, you know. So just using some life-specific examples, there’s, I think it’s 2% or 3% of all accelerated policies should have been declined. Which means carriers are taking on just a lot more risk than they were anticipating. There’s all these mortality slippage studies. I just came out from a bunch of the reinsurers. So I think it’s top of mind now, are becoming top of mind for a lot of the carriers. That’s the trend that you’re seeing. The realizing this problem is, is different than or bigger than they initially thought. And, you know, to your point, they’re starting to figure out new tools, new solutions and, you know, ways to try to push back and save their bottom line.

Jason Kozlowski: Absolutely. So one of the things I did want to ask you, too, is, you talked a little bit, you’ve used some good examples with the smoking nondisclosure in the smokers amnesia, as you called it. I think, you mentioned, changes to their weight during the application process. I’m just kind of wondering, what additional in digital behaviors, if you will, kind of signal that potential misrepresentation? Like what other types of things are, are carriers looking at, using your tools, to help them determine that?

Woody Klemmer: Yeah. So they’re really looking at, you know, we call them the hips, the high impact premium questions, the ones that really make a difference. I’ve listed a couple, you know, alcohol, smoking, BMI, but family history, medical history, avocation. You know, there’s a lot of questions that can result in, you know, different class codes or, you know, outright eligibility for a policy. And we’re looking at, you know, the behavior, we’re capturing a lot of behavior. So it’s really not as simple as just saying, you know, did they change their answer from yes to no? There’s a ton that goes into it. How much time are they spending? There’s like a whole concept of hesitation in cognitive load and all these different data points that all, feed into overall, you know, what the signal is for the carrier. And what we’re doing is, is and one other interesting thing is, and I’ll just use the smoking example, we might have a signal just oversimplifying that says did they click yes and then click no. What we have seen is that it’s not a lot of the carriers think, okay, I want to set up a smoking signal and only look at, you know, if it fires, only look at the smoking, you know, do the lab test or the coding test or whatever for smoking. And what we’ve learned is, it’s not always apples to apples. Like if somebody manipulates their BMI, it isn’t always necessarily correlated to the fact that they’re lying about their weight. But what we’ve seen is, is it’s much more likely they are lying about something on the application.

Jason Kozlowski: Interesting.

Woody Klemmer: What we typically do with carriers is say, don’t look at it again one to one, where if it’s an alcohol, do alcohol, or smoking, do smoking. Further qualification, it’s really passing them through. And the way that carriers are using us is more of a triage tool to say, we’re going to further qualify this person or take them through full underwriting. And what we try to do is find it, tune it so finely that there’s really no, we’re not hurting their accelerated rate. We’re actually helping improve it. We’re just helping them pull the people out of line that, you know, deserve it, sort of speak. And what they’re finding, again, is, is that there’s just a higher chance of something flagging. You know, the analogy I use a lot of time is like going through the airport at TSA. Right now, they’re doing it where, you know, you go through the metal detector in, like every sixth or seventh person gets randomly selected and pulled out of line. And we operate a lot more like the bag scanner, where we’re looking at every single application under an x-ray and saying, we think there’s a higher chance that there’s something funny going on with this one. Pull it out line so you’re not doing it randomly. You know, you’re doing it really more prescriptively, and we’ve found that the success rate there is a lot higher.

Jason Kozlowski: Gotcha. Now that’s, that’s really interesting. I like what you said about how they’re you know, not necessarily 1 to 1 it, you know, if you’ve lied about, potentially lied about something, and then, you know, there was some nondisclosure that there’s, the higher likelihood that something else, you may have not been 100% truthful about as well.

So that’s, that’s good. So one other thing I wanted to kind of ask before we wrap up, is, you talked about, kind of the customer experience, how are insurers leveraging, all of these insights and helping improve that fraud detection, and making it seamless, you know, without adding any of that friction to that customer experience?

Woody Klemmer: Yeah, well, I guess, the way that we always think about the holy grail of these digital experiences is removing friction and creating a better experience without increasing risk. And I think forever, that’s been a seesaw. They’re really inversely proportional, like the way that you improve the UX is you add or you remove friction, which inherently increases risk. It works the same way in reverse, where you know, if you want to tighten up your risk and fraud measures, you add friction, which lowers the customer experience. We want to try to help carriers create a, you can have your cake and eat it too, like you can provide a better digital experience, but also tighten up your risk and fraud at the same time. And that’s super important because, you know, like just beating the other analogy to death, you’ve, who hasn’t been at an airport and been randomly pulled out of line and you’re like, it’s the worst, you know, I’m running late for my flight, I needed to get a coffee. It’s just a bad experience.

Jason Kozlowski: Right!

Woody Klemmer: And it’s the same thing for insurance applications, where you started filling out an application and all of a sudden, you get that technical error screen and it says, oh, you have to go speak to an agent. You’re like, I just spent all this time filling out the application, and now you’re telling me I can’t buy? It’s a, it’s a bad user experience.

Jason Kozlowski: Sure!

Woody Klemmer: [It] leaves a poor taste in customers’ mouths. So the best way to do it is, again, you can’t, you can’t remove friction for everybody. Otherwise, you will have a really poor business. But if you can selectively pick the people that deserve the further qualification or that you have a higher chance of, you know, finding something versus the ones that are your genuine low-risk applicants, like accelerate those users and then do the full underwriting on the others. That’s what we’re really, that’s our main goal. That’s the ultimate goal that we’re trying to help carriers accomplish.

Jason Kozlowski: That makes perfect sense. Well, I just wanted to thank you, Woody. I know we’re about out of time here. Really been great having you on. I think I can speak for myself, you know, and hopefully our audience, when I say that, we’re definitely starting to look at fraud differently than we have in the past. And just from what I’ve learned talking to you, today and in the past, it’s really interesting, to learn about how that data can really provide [those] necessary clues and, you know, insight, for, for our carriers. And I do think that carriers are really starting to make a lot of strides in that area, you know, in largely in part to what ForMotiv is doing. It’s kind of like putting that puzzle together when all those clues are starting to come in and, it can really help carriers, especially as they start to move away from maybe the traditional ways that they used to do things where, you had a, a very static, agent amount table that would drive things like their requirements that, that they would order. Now they can be kind of, very dynamic based on the signals and the things that are coming in. So I think, it’s really exciting to see some of those changes that you’re helping [to] facilitate in the space.

To our listeners, I just wanted to thank everyone for tuning in. It’s hard to believe that we’re already, moving into Q2 2025, but we do have a lot of exciting content, and more, podcasts and blogs and webinars and everything coming your way. And we do love hearing from you. If you have any comments, and we’d love for you to follow us on social media. Please don’t hesitate to reach out through any of our channels. And please don’t forget to subscribe to the podcast! Stay tuned for the next episode of Sapiens Insurance 360. Bye for now!

The post The Soft Fraud Problem: It’s Bigger Than You Think appeared first on Sapiens.

We’re well now into 2025, and it’s been firmly established that the path of the future of insurance leads through AI. AI has been helping insurers with the claims journey, underwriting, customer engagement, and much more. Sapiens incorporates this technology in our intelligence platform and in our data and digital solution. I’m so happy to invite my colleague to speak with me here today about our AI approach and how we empower insurance. Gil Trotino, he’s the Director of Product Marketing, Cloud & Portfolio. Gil brings with him over 20 years of technical and business experience and enterprise software market. He’s responsible for developing and marketing the Sapiens insurance platform approach and offering, including market analysis, practice, product roadmap, and future vision. And he’s my preferred partner for lunch.

Gil Trotino: Thank you so much, Hili! Really great to be back here on the program, especially with you. Let’s tell the audience that Hili and I joined Sapiens together and I can share that she, Hili, has 20 years of product marketing experience also in the enterprise software market. She’s responsible for developing and marketing the Sapiens data, digital, and AI strategy and offering, roadmap, and vision. And she even finds some time in between to teach in the Reichman University. So Hili, I know that you’ve researched very thoroughly the AI spectrum for the last few months. Can you share a little bit about what you know about AI in the insurance world?

Hili Avi: Absolutely. But we can’t talk about AI without mentioning its founding father, Alan Turing, who dared to ask the question, can machines think? Seventeen years later, the answer is absolutely, yes. And let’s dive into the insurance industry. AI is transforming the insurance industry across multiple dimensions, efficiency, decision-making, and of course customer experience and risk assessment, even on every back-end processes. As its core, insurance is about managing risk, and AI is helping insurance to do that with greater accuracy and speed. From what I saw in my research, the insurance industry is very, very curious about AI from building role description with the help of ChatGPT and automating employer onboarding through building marketing campaigns solely with AI. So they’re very, very invested. One of the biggest shifts we are seeing is in claim processing. Traditionally, claims can be slow and manual, but with AI-driven automation and predictive analytics, insurance can expedite claim assessment, detect fraud, and even process straightforward claims in real time through straightforward processing. GenAI adds another layer here by helping with claims documentation, decision support, and customer communication. For example, something hot from my table right now, it’s claims of critical illness. This is a very specific issue on claims. These specific claims are processed and fully managed by humans due to its complexity and sensitivity. What if we can automate that process with AI, [get a] business ruling, and the customer will get paid in 24 hours. Think how life-changing it could be to him or her. Literally life-changing. Another area where AI is making a significant impact in underwriting, AI-driven models analyze a vast amount of data from structural policy, policyholder data information to unstructured sources like medical records, social media, or even the internet of things to refine risk assessment and pricing. This is not only making underwriting faster, but more personalized. Customer engagement is also being transformed. AI-powered chatbots in a virtual assistant are streamlining interaction, answering questions about policy, and even guiding users through complex processes like claim filling. AI is not just making insurance more efficient, it’s making them more customer-centric. I can give you a personal example. By the way, last June I bought a new car, and I was waiting on the phone with my insurer for 24 minutes to update my policy with my new car. I couldn’t leave the shop with my new car because I wasn’t insured. So if they only knew about the AI! At Sapiens, we are embedding AI to help insurance harness the capability, this capability and efficiency into every touchpoint from our core system to a persona-based application like agent application or underwrite application. And the list goes on and on, whether it’s through AI, power insight, decision automation, or intelligence system integrate [ed] into core systems, we’re enabling insurance to be more agile, data-driven, and responsive to the market demands. So AI in insurance, it’s not a trend, it’s a fundamental shift of how redefining how the industry operates and at the same pace, of course, and making sure our customers stay ahead of that.

Gil Trotino: I do hope that when you buy your next car, it’ll take like 24 seconds, and not 24 minutes to issue your car insurance. But you started to touch on this, but let’s talk a little bit about AI at Sapiens. Can you share a little bit about what is the vision and what is the Sapiens strategic approach to deal with artificial intelligence?

Hili Avi: Sapiens’ vision for AI is centered around empowering insurance with intelligence, data-driven decision-making, and automation to transform the way they operate. We call that the “GenAI Everywhere.” We see AI not as a feature function, but as an enabler, deeply embedded into our platform and solution that drives efficiency, accuracy, and of course, business growth. The copilot is everywhere. It is a fact at Sapiens. Over the past year, I have researched the subject in depth, spoken with our customers, and identified the places where AI is needed and where it can provide the greatest benefit. And of course, we have [a] few pillars in our strategic approach of AI based on that research. One of them, of course, is embedded AI across our insurance lifecycle. We’re integrating AI within our core processing, of course, claim automation, underwriting, policy servicing, customer engagement. We are, by embedding AI into our workflow and streamlining operation, we’ll reduce manual efforts and improve the overall experience of both insurance and policyholders.

Think about it. How about opening [a] claim in a minute after you’ve been involved in a car accident with WhatsApp and this claim is being processed while you are driving your way home? And I’m not dreaming, this is in my roadmap. Another pillar is that data-driven insight and hyper-automation AI is not only powerful as the data is behind that. That’s why we focus on leveraging structured and unstructured data, combining with advanced analytics, to drive real-time insight. Wherever it’s detecting fraud, optimizing pricing models, or even accelerating claim processing, AI enables insurance to make faster, smarter, and more accurate decisions. Think about it, automating document management by classifying and mapping letters and documents, mapping them into relevant claim and policy, or even using AI to expedite system setup process. Again, this, I’m not dreaming, this is in my roadmap. We do believe at Sapiens that AI should be practical, actionable, and build on the real-world insurance challenges. That’s why our approach is to productize AI within our platform, making it accessible, scalable, and made to deliver tangible business value for insurance today and in the future. I just need to point out, of course, we are sure our model is aligned with AI, ethical AI principles providing governance, while maintaining customer trust.

Gil, I’ve talked too much, [so] back to you. How does Sapiens intend to integrate into our platform? Because we announced the platform last June. Can you please remind us what [it] was it all about?

Gil Trotino: Yeah, sure. Absolutely. So yeah, you are right. Just June 2024, we launched the Sapiens insurance platform. Let’s remind our audience, what is it all about? So the platform actually encompasses whatever we do at Sapiens, okay? The entire Sapiens offering. And it’s more importantly, it’s illustrating the way the modular open and integrated way, and approach for us when it comes to developing and delivering business solutions to the market. So the platform includes all our core insurance capabilities across all the lines of business we support. Property and casualty, Life, Pension and Annuities, Workers’ Compensation, and more. It includes also the common technology engines like AI, data intelligence, digital engagement, automation, and more. And of course, a wide set of unified tools that we use to secure and operate our solutions. So the platform is everything we do and everything we deliver to our customers. And we like at Sapiens, for simplicity, to call the pillars of the platform by the letters A, B, C, D, where for ‘A,’ it’s all about AI. Our topic today, and automation, ‘B,’ is about the business solutions we deliver, the end-to-end, ready-to-deploy integrated solutions. ‘C’ stands for common foundations across all our solutions. And ‘D,’ finally, is about the combination of digital engagement and data, which is all about personalization.

Hili Avi: I love the digital and data! How does AI fit into our insurance platform? What is the capability we will see in the coming release of the platform?

Gil Trotino: Right? So as you just rightfully mentioned earlier, for Sapiens, AI is much more than a feature or capability that we develop or deliver. What we do is we are embedding and integrating AI and generative AI across the Sapiens platform. So what we did is we mapped the entire insurance value chain and now step by step, we are integrating those capabilities into different business processes and different personas. So it’s going to cover sales and marketing policy, admin, underwriting, claim management, customer service, everything to drive efficiency and automation. And maybe I can just name [a] few, provide some examples of what we already delivered and some things that we are going to deliver during 2025. So it’s starting with a set of 13 machine learning models which have developed, and we are integrating across multiple solutions. This is all about helping the agents mainly to make better business decisions and improve customer experience. So we talk here about generating insights about customer lifetime value recommendations for [the] next best offering, buying likelihood of customers, and more. When it comes to Generative AI, again, various tools which are integrated across the platform. One tool is called Document AI. Okay, so it’s all about enabling all the users of our solutions to summarize documents very easily, documents from different types, and chat with the documents using Q and A. So it can be the underwriter, who is quickly extracting key insights from policy documents. It can also be the claim handler, who can instantly retrieve policy details and coverage terms while processing claims, summarizing claim histories, etc. Another tool called Answer AI, also based on Generative AI, this is all about interacting with data. We have a very major component in our platform called DataSuite, which serves as our single source of truth integrating data across multiple sources. Now, Answer AI is the component that enables users for our solutions to interact with this data repository in an intelligent way, and ask all sorts of questions and queries about data so they can query about policies, claims, customer information and more. And finally, I can mention another tool, which is again, common tool, common engine. This is called Decision AI. It’s something we have for a long time. It’s the Sapiens-leading, no-code decision automation software, which enables automation and agility by applying and managing business logic, which is separated from the applications. So it can be, again, used for claim automation, underwriting automation, etc. And what we did recently, is we integrated Decision AI with Generative AI. So today, instead of the business user going to define all the business logic within our decision software today, decision can automatically generate the decision model from virtually any source written in conversational English. And this again, can be applied [to] policies, claims, and more, therefore, increase the level of automation even higher. So everything comes very nicely together. And if I can just give an example, going back to the platform, let’s talk about one of our recent business solutions. This is the small medium business solution that we just launched as part of our Winter 2024 platform release. So this solution, which includes our capabilities, but also some ecosystem partner that we use for data enrichment delivers a real-time view for the agent on customer insights and empowers the agents with the tools they need to upsell, cross-sell, and enhance customer experience. So we brought in the ML models, Generative AI, and other tools just in order to help the agents. And actually it gives this single agent the power like 10 agents, and it allows the agent, of course, to make his work much more efficient, more automated, and improve experience. Ultimately for our customers, the insurers, it’s really a great asset to unlock the small/medium business market.

Hili Avi: I remember that day when you launched the SME solution. It was a very good day.

Gil Trotino: It was, yeah, it was! And Hili, I know we can talk forever about AI, but it’s really a little bit, also, about the time. I’d like you to spend a few minutes, maybe to tell us a little bit about what’s next? So, how will AI impact the insurance domain, let’s say the next two to three years? And maybe you can tell us, what do you think, who will be the winners and losers of this innovative technology?

Hili Avi: It’s funny, because you know, Gil, every weekly meeting we have with our boss, Alex, I end it with the same sentence. While we were brainstorming here, something amazing happened out there with AI. And by the way, it’s true, it’s true! AI in the insurance industry is a reality. And over the next two or three years, we’ll see an acceleration of transformation. I do believe that in the next five years from now, there’ll be two types of companies: those who embraced AI, and those who resized. And insurance is evolving in three critical areas. Hyperautomation, as I already mentioned, enhanced risk assessment, and personalized customer interaction. Of course, hyperautomation will streamline claim processing and underwriting and of course, reduce manual intervention and accelerate straightforward processing. AI-driven insight will refine risk assessment, helping insurance price policy accurately and mitigate fraud. And on the customer front, of course, AI-powered chatbots, visual assistance and recommendation engine will make interaction more intuitive and responsive. Now, who will be the winner? Who will be the losers? The winner, as I said, will be the insurers who embrace AI strategically, not just [as] a tech add-on, but a fundamental enabler of efficiency and innovation. The GenAI everywhere, as we call it, those who invest in data-driven, decision-making, AI-powered claims automation, and embedded intelligence into the operation will gain significant competitive edge. Companies that leverage AI to enhance their customer experience, reduce cost, and drive agility will lead the market. On the other hand, insurers that will resist change, rely on outdated legacy systems, or fail to integrate AI into the digital transformation strategy risk falling behind. Hence, resizing. The industry is shifting from [a] traditional, rule-based model to an intelligence-adaptive system. Those who don’t invest in AI-powered platforms, like what we at Sapiens are building, may struggle with inefficient, increased operational costs and diminishing competitive position. Of course at Sapiens, we are focused [on] and ensuring our customer will be on the winning side of AI adoption. Our approach integrates AI across every lifecycle process, from policy administration, underwriting claims, and of course, customer engagement. We are helping them adapt scale and stay ahead of the curve in the new era of intelligence insurance.

Gil Trotino: Sounds fantastic. Hili. Thank you so much. You’ve given us so many expert insights to think about and as we know…

Hili Avi: My pleasure!

Gil Trotino: It’s an exciting time to be in the insurance domains and to see where AI can take us and take Sapiens customers over the next several years. So hopefully, you can join us again soon to comment on how it’s going! And to our listeners, thank you so much for listening. It’s only the first quarter of 2025, but we have so much more exciting content and commentary heading your way! So stay tuned and of course, we love hearing from you. So if you have comments and if you’d like to follow us on social media, please reach out to us on our channels and don’t forget to subscribe to this podcast and stay tuned for our next episode of Sapiens Insurance 360. Bye for now!

The post Sapiens’ AI Approach appeared first on Sapiens.

In the everyday experience of payments, like utilities and groceries, have you, the policyholder, ever sat down to think about the deeper value of life insurance beyond the policy details? That beyond the policies and premiums lies a deeper purpose to life insurance – one where families are given the tools to navigate life’s toughest events. Often, the most unexpected.

Today’s guest is Ron Gura, Co-Founder and CEO of Empathy, the world’s leading support system for navigating loss platform that combines technology and human support professionals to provide emotional and practical support after the loss of loved ones. Ron is a tech entrepreneur who has brought his love for developing empowering products to startups and major international corporations alike. Before launching Empathy in 2020, Ron held roles as a Product Executive at WeWork and eBay. He initially joined eBay after the acquisition of The Gifts Project in 2011, a social E-commerce startup where he served as a Co-Founder & CEO.  Ron, welcome to the program. I am excited to hear about your vision and journey of Empathy!

Ron Gura: Thank you, Calvin. It’s great to be here!

Calvin Zhai: Great, so let’s start by first talking about the original role of life insurance. As we all know, its expressed purpose is to provide financial security for families after a loss. How do you change that transactional expectation and why should a company attempt to do so?

Ron Gura: Absolutely. Well, let’s start with that important point you hit on right there. How do you take a transaction and shift it to our relationship? I think that’s the big question. We are working, and we’re talking right now in the midst of the greatest wealth transfer. Trillions of dollars are moving hands. A third of them, give or take, in life interest premiums. And life insurance companies are just losing AUM because there’s nothing from a user experience standpoint or value-add standpoint, they can do about generation loyalty and asset retention when it’s too late, when the beneficiary who is not the policyholder, unlike most adjacent insurance industries, is just coming away and rightfully taking the funds and moving on, after such a meaningful life event. So what we do is we have a comprehensive, on-demand system that offers grieving families the full range of grief and estate needs. And with that, we offer continuity of care, which leads to asset retention and generational loyalty.

Calvin Zhai: Thanks for that, Ron. So as we know, the life [insurance] industry has traditionally been lagging behind and slow to adopt new technology. What barriers have you faced in bringing a new service model of life insurance to the forefront and how have you overcome them?

Ron Gura: The first thing, I want to give the life insurance industry a little bit of slack. I know some of my best friends, some of your best friends in the life insurance business, and it’s true, they’re not the fastest. But let’s admit it, if someone gets some slack for being risk averse, it’s the life insurance folks because they’re supposed to weather the storm, they’re supposed to avoid mistakes. And what we’ve seen, especially after partnering with more than 30 life insurance carriers, is that they’re really tough on implementation. It really was a big unlock for us to create a situation where we can shift from a deep implementation to a life configuration and just add the empathy touchpoint in a multifaceted way without the need for heavy data transfers and deep integrations with these life insurance carriers.

Calvin Zhai: That’s really interesting, Ron. In light of your previous answer, what lesson can insurance professionals, HR leaders, and financial advisors, take from your model in terms of planning technology and the human component to deliver value to families in their time of need?

Ron Gura: Well, I think it’s about mixing the two. I think there’s no just binary solution when it comes to an infrequent and meaningful life event like a loss. It’s not just technology, it’s not just humans. It’s also not just grief and emotional support, and it’s not just financial and administrative work. Fundamentally, we believe that grief is made hard by logistics, and logistics are made harder by grief. So when you put a cohesive solution in the market, you simply let machines do what machines do really well, like pre-filling forms using GenAI to take away the mundane and doing your financials. Things we use technology for day in and day out. And we let people do what people do best. Being on the other side of the line, showing up with compassion. So it’s that mix that we bring to the market and we believe that not just carriers and tech companies should use it, but also financial advisors, brokers, everyone.

Calvin Zhai: Great. Now, your company, Empathy, combines cutting-edge technology with human care teams. How does this approach improve the customer experience, and why do you think it resonates with both life insurance carriers and policyholders?

Ron Gura: So we set out to create a new standard for supporting families through life’s most difficult moments, and we use technology to make it sustainable and scalable. By offering continuity of care to a beneficiary, you’re not just helping the beneficiary, you’re also adding peace of mind to the policyholder, who before that got financial peace of mind, but now, they know that their carrier is also providing emotional peace of mind and administrative peace of mind on top, because they’re going to show up to the beneficiary at that moment of truth. So if you oversimplify what we do from a user experience standpoint, you can look at a claim call of I lost my loved one, where’s my money, in so many different words. And then, sorry for your loss, your check is in the mail, but we’re not going anywhere. We’re going to stick around with you in the days, weeks, and months.

Calvin Zhai: Thanks Ron. Thanks for sharing that, the valuable insights. So to wrap things up, how do you see technology further enhancing the way families plan for the future and engage with their insurers? Say for example, addressing the gap between traditional estate planning tools and what families really need?

Ron Gura: Yeah, Calvin, we talked about estate settlement, we talked about aid, need, but you’re right, technology could be used and should be used before as well. One of the things that is going to help families the most is actually having their loved ones do some pre-planning ahead of time and just exactly why we launched together with New York Life on stage [at] ITC last October, the LifeVault, the most comprehensive estate planning solution. So feel free to check it out on Empathy.com. But basically what it is, is a very straightforward way to leverage technology to create these legal documents for you. We’re very proud that we are able to add peace of mind from that angle as well.

Calvin Zhai: Ron, thank you so much for your thoughts and for taking the time to appear on the podcast today. Your insights on the importance of combining technology and human support to build connections with families are so impactful and refreshing. I’m sure that our listeners are also impressed by this new framework of life insurance coverage and service, and I hope you can come back again in due time to update us on how it’s working out.

To our listeners, as always, we love hearing from you, so if you have any comments or would like to follow us on social media, please reach out to us on our channels. And don’t forget to subscribe to the podcast. We’ve got so much more coming this year, so stay tuned to our Sapiens Insurance 360 podcast. Bye now!

The post Life Insurance 2.0: Helping Families Navigate Life’s Toughest Moments appeared first on Sapiens.

Dawid Kopczyk: Hi everyone. Thanks, Amanda, for inviting me to the podcast!

Amanda Ingram: Well, let’s get started. Dawid, we’ve got a lot to talk about. So speaking of another famous couple, are AI and machine learning, and we always call it ML, these days, still viewed as buzzwords in pricing or are they now fully integrated and delivering measurable value?

Dawid Kopczyk: That’s a good question. I believe there are two sides of the same coin. So yes, the AI is a buzzword, especially these days, and particularly when you are thinking about the usage of something called GenAI in insurance pricing. On the other hand, we have I think, have [a] handful [of] examples that AI and machine learning are already delivering value in the insurance pricing. So on the buzzword side, there are always too high expectations when it comes to what technology can do in the next year, whereas the past experience shows us that it takes around five to 10 years to fully utilize the benefits of any technology. So it was like that with [the] e-commerce bubble at the beginning of 2000, and my guess is that similar things are happening with GenAI and AI. If there is a vision that AI will calculate all of the prices for insurance pricing without any help of the insurance pricing teams and it will do that on its own, even in the next three years, then I think it is [the] completely wrong picture. But we see already the first usages of AI supporting underwriting decisions. We can also see the examples of usage of the AI in the insurance pricing, but it’s not going to be like that. It’s going to be fully automated in the next five years or even 10 years, and if we concentrate on these positive sides, then as I said, AI already delivering the value, but this is not in a fully automated mode. This is always supporting the pricing teams. So we see it firsthand because actually AI and machine learning techniques are used in Quantee software, and the insurers are gaining the competitive advantage thanks to that. So examples from the UK market are insurers investing in machine learning models to better predict, predict risks, sales discounts, policyholder behaviors. So they use already sophisticated modeling techniques that includes AI and machine learning algorithms to drive the results better, to improve the loss ratio combination that’s actually working. AI is also spinning up tedious tasks like preparing risk factors, clustering big data sets like for telematics, spotting patterns, [and] also in the portfolio monitoring tasks when it comes to the insurance pricing. So we can see also the value [brought] by AI, with automating the tedious tasks and that makes the pricing actuaries, pricing analysts, it makes them free to do more scenarios, to do more analysis, and more scenarios and more analysis. It drives the better results. So to sum up, so the answer is that yes, the AI is the buzzword, we have to be careful with that. On the other hand, we can see already the value that AI brings, and I believe that the insurance companies that will not invest the proper time to actually investigate how to use this AI and machine learning properly, insurance pricing, they will fall behind or they will easily lose the competitive advantage.

Amanda Ingram: It’s a fascinating topic, isn’t it Dawid? I mean, I’m just back from a three-day conference and everybody is talking about AI and the impact that it’s having. And I totally agree with you taking the time to understand its capabilities is essential. But do you think that insurers have shown a clear shift when it comes to deploying pricing models over rating tables? And how do you think that’s driving change, particularly when we look at the inclusion of AI in some of those processes?

Dawid Kopczyk: I think the short answer is absolutely, yes. So insurers, there’s a clear shift toward deploying the pricing models faster and faster, and doing that more sophisticated that ratings. And to be honest, most of the customers that we are talking to are actually coming with the same issue. So they have the outdated rating tables approach. They wanted to change that. They see that they are losing the competitive edge on the market, and they want to react to the changing environment, to the movements in the prices in the market. They wanted to react with something more sophisticated than a set of the rating tables, which is deployed rarely or you are rarely limited in terms of the pace of the deployment of the pricing updates. And I think there are three main drivers [as to] why it is changing. So I think I mentioned, I read the first one, but insurers realizing that they’re just simply falling behind the market, they’re constrained by the legacy systems when it comes to deployment of pricing app base to the distribution challenge. So that’s the reason number one, that’s the driver number one. Driver number two is that the pricing department usually has already the ideas [on] how to respond on what is happening in the market, how to respond to the regulatory change, or how to respond to the competitors’ movement in premiums for a specific segment. So they already know how to react, they know how to change the models to be better, but then they’re somehow stuck and they just cannot deploy these new ideas. They cannot connect this to the distribution channels or to the policy admin systems, and that actually drives them to make a decision to use something more sophisticated from the IT perspective. And the third thing is that usually there are blockers in terms of how fast pricing teams can use new data or new risk factors, whether they are limited to a simple set of the rating tables or they can use more complex structures and models and how often they can perform these changes. So these blockers are usually imposed by some IT-like systems and I think it’s becoming a strategy of many interests right now to remove these blockers. The key challenge. It’s…

Amanda Ingram: Fascinating, isn’t it?

Dawid Kopczyk: Yeah, it is. And..

Amanda Ingram: Go ahead Dave, sorry to interrupt you.

Dawid Kopczyk: I think insurers are starting to realize that. I think the key challenge is that the real clue is to completely link the design phase of the pricing models with the deployment. So you cannot really tell apart those two words and they have to be integrated. This is extremely difficult to build such a solution. And I don’t think that insurers are software companies that are, maybe they are capable to build that, but then there’s a different story to maintain that. And I believe that here it’s where Quantee comes into the play. It perfectly integrates with the distribution channels and policy admin systems like Sapiens to deliver value constantly and make, just allow the pricing teams to design whatever the pricing models they wish to design and then deploy it to the distribution channels.

Amanda Ingram: I think pricing and certainly pricing modeling and actuarial processes are quite complex. Anything that helps improve and allows that agility within pricing and actuarial modeling is really important. Of course, we’re aware that profitability remains a primary objective for insurers, but does deploying actuarial models, pricing models help improve profit margins? What’s your take on that?

Dawid Kopczyk: Yeah, this is an excellent question. The short answer is again, yes, so how to link being more profitable with being more agile? And I think we can spend some time to explain that. Firstly, we know that the more precise and personalized individualized models we have, the better we are when it comes to loss ratio and combined ratio in reality. Now, if we have limited ourselves by a set of the rating tables and kind of a slow deployment process, then we just cannot deploy these things because it’s usually very difficult to convert some sophisticated pricing models to the set of the rating tables, because we lose accuracy, we lose this segmentation benefits thanks to the more sophisticated models, and then we will be definitely falling behind in terms of the business KPIs in the market. That includes loss ratio and combined ratio. So if you have a reduction of the time to market to deploy such a precise and personalized model, then that’s basically your profitability goal. And secondly, the speed of deployment. So this is especially relevant to the European markets or LatAm markets, how frequently we can update our pricing engines gives us the agility to quickly respond to whatever is happening in the market. So if we have the system behind the insurance pricing that allow us to quickly respond to quickly change the pricing models, then we are able to correct underperforming segments in real time. We can stage A/B testing for specific segments, and we can react to the competitive movements. And this way we can drive our profitability up thanks to the speed of the deployment.

Amanda Ingram: I think the market is such a dynamic place now, isn’t it? Insurance market itself, consumers are a lot more savvy. Everybody’s looking for the better price, and with insurers developing newer and newer or more directed and focused products, this agility becomes really important, doesn’t it? And I think that growing demand for agility and flexibility in the pricing process is really starting to come to the fore now. So how does an external pricing engine such as Quantee help to deliver those benefits?

Dawid Kopczyk: Before funding Quantee, I was an actuary, so actuaries, they wanted to always tweak something. So they’re never fully satisfied with the external software provided. There’s always a better strategy to do something more customized, more flexible, and we knew that already, that this flexibility is actually one of the requirements and it has to be incorporated into any software that you sell to the insurance business. And so with this growing demand for the agility and flexibility, I think this is already a clue that I mentioned earlier. So the key challenge is that you have to link the designing of the pricing model, and it has to be really flexible. It has to be really allowing to design any pricing models that pricing teams design to answer to any market changes, like changes in the prices of competitors or regulatory changes. And you have to link that with the deployment to the distribution channels and policy admin systems. And if you know how to do that, then you can truly unblock the pricing teams to build whatever they wish and drive the profitability results, loss ratio, and combined ratio.

Amanda Ingram: It’s fascinating. We could spend hours talking about this and it’s been really great talking to you today, Dawid. Thank you very, very much for those insights and your perspective on that. It’s really becoming quite a hot topic. AI is touching pretty much everything I think now, but we really do appreciate you taking the time to speak with us today and to share your insights with our audience. Thank you.

Dawid Kopczyk: Thank you, Amanda, and thanks for listening.

Amanda Ingram: And to our listeners, of course, thank you so much for tuning in. We always love to hear from you, so if you do have any comments or you would like to follow us on social media, please reach out to us on our channels and don’t forget to subscribe to the podcast. We’ve got a lot more and many more exciting subjects ahead. So stay tuned and be on the lookout for our next segment of Sapiens Insurance 360. Bye for now!

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Today’s topic is a great one. It’s geocoding. What is it and why is it important? Today’s geocoding technology is so much more than just location intelligence; it allows underwriters to collect valuable data for underwriting processes and uncover opportunities for growth, as well as identifying risk. And here to expand on this valuable capability is Berk Charlton, Chief Product Officer for Smarty.  Smarty, a valued Sapiens partner, is an expert location data intelligence firm whose technology verifies, validates, enriches, standardizes, and auto-completes addresses in 240+ countries and territories around the world.

Berk, welcome to the program!

Berk Charlton: Thanks Andy! I’m happy to be here. And Smarty is just thrilled to be part of the Sapiens’ ecosystem and a partner.

Andy Labrot: Well, it’s great to have you here, so let’s begin. So what should insurers be looking for in a location intelligence solution?

Berk Charlton: Well, thanks, Andy. The location tells us.. [it’s] a really, really big, it’s really very large, definition. Our specialty in location intelligence is, is anything that begins or ends with an address, we want to be able to locate it properly and help our customers make decisions about it. So one of the first things that everyone should be looking for is a high level of accuracy. In our case. rooftop accuracy is the standard. Most addresses in the U.S. and many throughout the world will be accurate to the building footprint or the building rooftop. Being easy to integrate is also critical. I’ll get into that a little bit more. And then reliability including, since we’re 100% cloud native, having a high level of uptime, in our case, five nines. And in fact, we’ve actually had never any recorded downtime in over 11 years. And then having consistent results over time with the answers that our customers are expecting, and also great support. When if you call us, we will answer the phone, we will answer chats, we answer emails all within usually within minutes. But our SLA is 24 hours. Most insurers, also use multiple data providers. That’s, that’s a common thing that they would need to do. They’ll, they’ll use some risk data from one company, other risk data from another. But the thing that ties it all together really is the location. It’s a location not accurate that everything else becomes suspect. So and then having a way to integrate all this data together is really important. And that’s why our, our ease of use APIs are pretty critical to this process.

Andy Labrot: We at Sapiens can certainly attest to the ease of integration with Smarty, as it’s prepackaged with our CoreSuite for P&C solution. But why is accurate and scalable geocoding important in underwriting processes?

Berk Charlton: That’s a great question. I mean, as you said before, accuracy is the really the foundation of risk analysis as it applies to P&C insurance. And without an accurate geocode, the modeling results, underwriting and pricing, even things as basic as territories assignment, it all becomes suspect. The Harvard Business Review, for example, did a, a research article on accurate geocoding and they determined that hyper-accurate geocoding, which they determined as being accurate to the rooftop and unique ID assigned to every location and address, could, across the industry, save tens of billions of dollars or to add tens of billions of dollars in profitability. And then the common ID allows such a smart key that we have, allows you to link risk data across providers, to this very common ID.

Andy Labrot: Wow. That’s very powerful. So moving on, how can insurers and risk modelers get the most out of geocoding solutions?

Berk Charlton: To get the most out of it, first of all, I think that, that there needs to be a recognition that accuracy is important and that speed and integration are important. The one way that some of our customers have been able to do this is they might have a cascading process by which they say, well, if this one geocoding solution, gets the answer, we’ll take it. And then they’ll move on to, to maybe one or even two other providers. We don’t have enough hubris that we say, we’re going to get every address perfectly geocoded every time, but what we will tell you is that, but we are accurate 97% of the time, we’ll get to a rooftop or a parcel level. But what we’ll tell you is, we say we got an accurate address, we did get an accurate address. So our customers should be looking for, to understand the harm that false positives can give you. And I’ll use like, there’s a couple of very popular, mapping platforms, for example, on the internet that will, that people, very popularly use for routing and things like that. Well, the false positives, though, are quite legendary there. And a lot of insurers have realized that they can’t, they can’t use, consistently at high volumes, something like Google Maps because it’s not going to give you, it’s going to give you false positives and it won’t tell you it gave you false positive. So insurers need to, to combine and combine geocoding with address validation. And that will definitely help reduce false positives and then have the confidence to move forward with that. And then also the ability to be able to link that data to a common unique identifier, such as master, that we have in our master address list, but it’s also included in all of our geocoding products, too. We assign a unique ID to every location. Then that can be used to, to look at… do I have multiple addresses that are all tied to the same unique ID? That means you’ll have, you’ll be able to make those determinations quite easily.

Andy Labrot: Fantastic! Well, we one of the things that we leverage from Smarty is the idea of the FIPS code, which helps us identify the counties which then allows our insurers to manage their capacity. But what are some of the other products that Smarty offers that are complimentary to geocoding technology and servicing?

Berk Charlton: Well, that’s a good question and thanks for asking that. We, I did already mention that we have our address validation, for the U.S. and for 240 countries around the world. That this will… the first critical element in terms of getting a good geocode is getting the address right. If you don’t get the address right, then the geocode becomes very suspect. And so a lot of our customers will use or use our, our address verification products, independent of geocoding, just so that they can, can help with, package delivery or with, with mail ability or just understanding their customer base a little better for fraud analysis and things like that. Some of the other products that we have with, would include our auto complete product. Whereas you start typing an address, [and] it will pre-fill it with the information about that particular address. And that is also a global product. And our property data for the U.S. which has 350 attributes of data for every single property and will have things like structure attributes and geographic attributes about that property and also even elevation. Our master address list is an important product that’s actually foundational to our other products. But that includes, over 210 million addresses. Also, I should have mentioned earlier that nonpostal addresses are really a critical thing for insurers to know that even if the USPS doesn’t recognize an address as being something that mail is delivered to, a non-postal address is still a valid address that many insurers need to know about. Our master address list product includes all of the non-postal addresses and all of the postal delivery addresses across the country. All, almost all of them accurate to within a building rooftop or a partial central level of accuracy. One other thing is, is we try to make our products very easy to use, we have plug-ins for Excel, Google Sheets, SQL server, QUIS, and, and more products. So we’re expanding that. We’re trying to make our products accessible in addition to being, available in a, in a platform like Sapiens. We realized some our customers may want to use the data in in other tools as well. And we try to make that very, very, available.

Andy Labrot: Wow. That’s a very, very powerful solution. So how does Smarty differentiate itself from other geocoding and location intelligence providers?

Berk Charlton: Well, we include a lot of metadata just in our standard results. So for example, a normal geocoding result will include over 47 attributes about that address, including things like county FIPS code, and, and if it’s a residential or commercial address, we include things like congressional districts and place codes and various other pieces of information that many insurers may, may find helpful. Our speed is something that is really important. We have customers that have, a contractual requirement. They need over 75,000 records to be geo-coded per second, which if you do the math on that, there’s hundreds of millions of records an hour. This is not unusual for our customers to be able to get these kinds of speeds. We’re cloud-native, so it’s not like we’re retrofitting, an on-premise solution to the cloud. We’re cloud-native, so that’s, that really helps us to be able to, to live and support and our customers completely in the cloud. And then Smarty Key is an important differentiator. It’s a unique identification code that applies to every single address in the whole country. And that’s included with all of our geocoding products.

Andy Labrot: Wow. That’s terrific. So thanks for all this great background information as well as your insights Berk, and for addressing and advising our listeners on how geocoding can identify property specific risks, improve risk assessment, and create more accurate pricing models to enhance operational efficiency. To our listeners, as always, thank you so much for spending your time with us today. We love hearing from you, so if you have any comments or would like to follow us on social media, please reach out to us on our channels. And obviously, don’t forget to subscribe to the podcast. We’ve got more coming, so stay tuned to our Sapiens Insurance 360 podcast.

The post Unlocking Insights: The Power of Geocoding in Insurance Underwriting appeared first on Sapiens.