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InsTech - insurance & innovation

11 Oct 2026 · 29m · 10 chapters

Episode artwork

John Hele & Greg Framke: Portage AI: The hard 20%: where AI could create the most value in insurance (420)

In short

Portage AI’s approach to applying AI to the “hard 20%” of insurance processing—custom-trained, production-ready models that automate complex, high-stakes workflows (especially post-bind processing and pricing submissions) with accuracy guarantees and secure deployment.

Guests

Greg Framke, CEO of Portage; technologist with 13 years in Silicon Valley disrupting trading/brokerage; ~10 years involved with insurance; co-led AI projects at Resolution Life. John Hele, executive chairman; life actuary background plus investment banking (M&A), chief risk officer, CFO roles, president/COO; led a $400M tech transformation at Resolution Life to bring processing in-house and save $150M/year; also involved in AI projects.

Key claims

choose the right AI tool per task; run behind client firewall; models trained on client data; audited/explainable outputs; “no value, no deal” MVP-to-production promise.

Notable examples

Bermuda post-bind processing for reinsurers; harmonizing data into a common ontology; extracting 100-page claim reports for predictive loss-ratio improvement; Go “Move 37” analogy for discovering early-game moves from large datasets.

Written by AI. May contain mistakes.

Chapters

0:45

Backgrounds of John and Greg

John and Greg share their diverse backgrounds and experiences in the insurance and technology sectors.

“here you are again launching a new business.”
2:55

Mutual Experiences and Joining Forces

Discussion on how John and Greg's past collaboration led to their current venture in AI within the insurance space.

“And the real reason we were able to do it was I happened to find Greg to join me and help me in this whole effort.”
5:15

Introducing Portage AI

John and Greg explain the purpose of Portage AI and its focus on automating complex processing problems in insurance.

“I think it's a combination of all those things.”
10:18

AI's Role in the Insurance Industry

Insight into how AI can transform insurance processes by solving complex data challenges and enhancing operational efficiency.

“Same classes of business that we find in London, obviously.”
12:44

Acquisition of InsureWave Assets

Discussion about Portage AI's acquisition of InsureWave's assets to enhance their service offerings in pricing and processing.

“that's when the real power will come forward.”
14:01

Strategic Acquisition in Insurance Technology

Explore the rationale behind acquiring InsureWave and its impact on pricing and processing.

“And tell us about why you bought that and then where it fits within your proposition now.”
17:26

Progress Report on Acquiring InsureWave

Discuss updates on the InsureWave acquisition and planned projects.

“I think given summer, everywhere, it's given us actually a reasonable amount of time to get ourselves organized.”
19:15

AI's Transformational Potential in Insurance

Examine the potential of AI in revolutionizing the insurance industry through real-world examples.

“What do you see as the potential of this technology in terms of what it's going to do to the insurance industry?”
23:06

Building Solutions vs. Consulting in AI

Contrast building tangible AI solutions with merely advising on technology.

“I'm probably more optimistic about the timescale for something like this happening.”
25:15

Final Insights and Call to Action

Encouragement to embrace AI's potential in business alongside an invitation for collaboration.

“And just to be clear, these are our solutions and our products, and we're not consultants, certainly from that point of view.”
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Transcript

Automatic transcript. May contain errors.

0:08Welcome to this week's Instech podcast.

0:11Robin Merttens: I'm joined today by Greg Framke, who's the CEO of Portage, and John Hele, who's the executive chairman. Welcome both.

0:19John Hele: Thank you, Robin. Appreciate you having us.

0:21Robin Merttens: Now, we've been doing these podcasts for about 10 years, and I'm accustomed to seeing fresh-faced, disruptive startups are going to change the world of insurance. And I'm going to be a bit brave early on. Am I the youngest person on this podcast? 66?

0:37John Hele: Maybe.

0:38Robin Merttens: Maybe. It's close. That's good enough for me. That's part of what I want to talk to you both about today, because you've been successful in business. You've built businesses before. here you are again launching a new business. In order to understand why you're doing it, we should talk about your antecedents, what your past looks like. John, why don't we start with you?

1:01Greg Framke: Sure. So I'm originally a life actuary startup, but did a wide variety of roles. I was an investment banker doing M &A transactions. I was a chief risk officer, a CFO at publicly traded large insurance companies and banks. I've been a president and COO as well. So really a wide range of jobs and a good amount of technology.

1:24John Hele: Greg, what's your background? I was fresh-faced and changing the world about 25 years ago when I went out to Silicon Valley and spent 13 years with a company that did disrupt the trading and brokerage and somewhat the banking industry. I had my turn at that. But I think by your question, we have seen some things and I think we've seen some things that have worked exceedingly well and we've seen things that we've learned from. So we kind of bring all of that approach to our present endeavor. But I've been a technologist my whole career, Wall Street, like I mentioned, out in California, and have been in and around and involved with the insurance industry for about 10 years in a couple of capacities.

2:04Robin Merttens: I didn't know how to do it diplomatically. I hope I got away with it. but you guys worked together before haven't you there you are co-founding what were you working

2:12Greg Framke: on together before i joined a firm resolution life and we had bought a large life insurance company in australia and new zealand as well as one in the u.s and we had to do a large technology transformation in that to extract all the processing from the other company and set up independent operations and historically resolution had always outsourced this to other people but we decided with the advancements in technology that we could do it ourselves and do it more effectively. So it was a very large project. It was$400 million, but to save$150 million a year. And we did it on time to budget, to spec over three and a half, four years.

2:55Greg Framke: And the real reason we were able to do it was I happened to find Greg to join me and help me in this whole effort. And I'll turn over to Greg to give his side of the project.

3:05John Hele: mutual admiration society. I met John and Sir Clive right before COVID lockdown and had enough experience with insurance, life insurance, large kind of multinational life insurances to appreciate the challenge. And like John said, we borrowed a playbook from my years in California. And so I think the experience of these really large-scale transformations, which included a number of AI projects. And I've personally been involved in AI 25 years now in some form or another. But particularly with the insurance companies that Resolution was buying around the world, we did a number of AI projects together.

3:45John Hele: And John and I were coincidentally leaving Resolution around the same time. I basically given ourselves a four-year run to get this project done, and we did. And that experience around AI and the advancements in the technology and the successes that we had at Resolution brought us together to say, let's bring that to the industry at large.

4:06Robin Merttens: So you're wise. There's a little bit of mutual admiration going on. You understand AI tech and its potential, but why go again? Is this driven by the desire to work together? Is it because you're inherently entrepreneurial and you don't feel as if you've quite had enough of it yet? Or can you just not face a life on the golf course? What's the motivation?

4:30Greg Framke: Probably a bit of all those. However, we believe firmly that AI is the biggest technology change of our lifetimes. And we've been around for a few years, as you've already said, but it's going to dwarf every other thing that we've seen before. And we were quite convinced of it, even from several years ago. When I retired the first time in 2018, I took a summer course because I had a garden leave all summer, a master's course from Columbia University in AI to understand the the mathematics behind how AI works. And what's happened since that course I took in 2018 and now is just simply breathtaking.

5:06Greg Framke: And we can do things now that took much longer when we did our projects at Resolution. So we're very excited about it. I think it's a combination of all those things. But we really wanted to be part of this fourth industrial revolution and really help companies do it because we were able to implement AI at scale and in production. and that's what we can do for people.

5:31John Hele: I'm not sure I can improve upon that answer. I, from my point of view, I'm still learning. I'm still very intellectually curious, but more for me, my whole career has been about applying technology to problems and driving value. I love technology. I can get excited about technology like any other technologist, but at the end of the day, it only matters what it can do. What can it do for you? What can it do for me? And I've like john see that where we are today and where we're going very much like early internet days by the way it's just there's a lot of corollaries the opportunities for companies to really change the way they're doing business and change the way they're thinking about business is pretty profound and i want to be a part of that and i want to help be part of that frankly

6:21Robin Merttens: we're 10 minutes in and we haven't talked about portage and what it is so this is this would be a very good time for you to tell us about what Portage does and what's the problem that's designed to solve.

6:33John Hele: So we formed this company to bring AI to automate the most complicated processing problems that we can find and that we can solve for clients. And in a world of 80-20, where maybe 80 % of the work is done, look, most industries are not 80 % of the way to nirvana or automation, But we like the 20%. We like the stuff that has been either not economically viable to transform or impossible to because the technology just wasn't there. So we custom train models for clients on their data. We support those models when we put them into production. and based on the experiences that we've had with AI projects over time, we want to tackle a real problem with a real solution and do that in a way that demonstrates value, period.

7:27John Hele: And that approach we will do with our capital. If we can't demonstrate value to a client, we'll shake hands, walk away, no harm, no foul. But because there's been so much hype around AI and so many failed attempts to get AI into production, we'd rather put our money where our mouth is and say, look, we'll do a minimum viable product. It's a production-ready model. It's trained on your data. We will demonstrate the value. If we can't solve that problem or prove that value, no problem. We'll take our toys and go home. But so far, we haven't had to do that.

8:02Greg Framke: I'd like to add that what further differentiates what we do is we know which AI tool to use for a particular application. And this is a very important element. We can do it securely. We do it behind your firewall, the client's firewall, or in a secure client-rented cloud environment. And we don't access code or routines that go outside of that. And that gives us high accuracy. You won't drift. It won't make up new answers for you. It tells you when it can't solve it. and that's very important because if it's the client's core processing data that 20 they've got to be able to rely on it it needs to be audited it needs to be explainable and there are ai tools that can do that and there are some that can't and you need to know when to apply the right tool for your problem and we guarantee our accuracy as greg said we guarantee that you get

8:57Robin Merttens: value i hear that and i think this i share your view that this is ai and genetic generative ai dicta have this sort of game-changing capability and then everybody did a whole series of pocs but they did them on simple stuff it's simple processes that they can automate you've gone to the other end of the spectrum and you're saying everyone else can play in that space but we are applying what we've learned over the years about AI to the most complicated things that you can do. We're going to throw these tools at your data sets and tell you things that you need to know or didn't even know you needed to know.

9:36Robin Merttens: And we'll do that in a way where we'll build it and turn it over to you and only if it works and is successful and builds value. Is that what you're telling me? Yes, got it in one, Robin. I'm quite good at working out what people do. It's just I never quite work out what to do with it. So give us an example of the kind of things that you either are doing or you can do for the insurance industry that falls into that category.

10:04John Hele: For the insurance industry, there's multiple use cases. I think one of the things that attracted us to the London opportunity, which we'll come to maybe a little later, is the post-buying processing and commercial specialty reinsurance in Bermuda. Okay. Same classes of business that we find in London, obviously. And this is just an area that has not been addressed. Pricing is kind of one side in the reinsurance world. There's various levels of technology that apply there. But when it comes to what happens after they have the business, it's still BPO spreadsheets and a lot of manual labor to basically take that information, extract what you need, and making sure that it gets to where it needs to go.

10:50John Hele: Now, that has a really great return for clients. AI, in this case, is just a better way of automating than maybe we could apply before. AI is just really good at extracting and harmonizing information, and it's very economical at this point in time. So that's just one area that we've been going after. But we'll talk more about what we think the big picture is here, because I think that by itself has a good ROI. We'll do those projects all day long. But that information, once it's structured and available for other software, could be AI, to look for patterns in, to help inform reinsurers, that becomes a loss ratio move.

11:35John Hele: So you're taking kind of this operational data that is really just a pain for most of the companies to deal with, right, and turning it into more of an offensive weapon. Most companies aren't set up for that right now because just the fundamental data is just not in a form where it can really help machines understand patterns. But we're convinced and we'll be happy to work with any client who would like to look at that because we think that's where it's going. And we're going to be there with the clients who want to work with us to do that.

12:07Greg Framke: The challenge has been historically that you've got all this data in various formats, but there's different language used for the same data elements often between different suppliers, brokers, or clients themselves. So to come up with that common language, the common ontology it's called, has been a great deal of work and effort. But AI is very good at this now. and finding the terms that mean the same thing and checking them and double-checking them. And when an insurer can get all that data and all those elements into a common ontology, that's when the real power will come forward. And this has been, I think every insurer's had a data-cleansing project.

12:50Greg Framke: I don't think anyone's ever finished them. But you can do this now, and we're really good at this. That's the starting point, and we think there's massive opportunity there. And then, as Greg said, the real end game is when you have that and have all that history and all the detailed history, not summarized, because you want to get all that detail, all the claim reports, all the detailed 100-page claim reports, all the key data elements extracted, stored. Then you can start applying very powerful predictive analytic tools to help you improve your loss ratio.

13:24Robin Merttens: Maybe that should be your strapline, your mission. mission. We'll finish for you your data sorting out projects that you started 20 years ago, spent tens of millions on and never quite finished. So that tells me that the more complicated, the better from your point of view. So specialty market, UK, given how much of it we have over here, Bermuda, US, is that going to be where you focus your attention?

13:49John Hele: Yeah, those three markets are our focus right now.

13:52Robin Merttens: And then in June this year, I noted that you bought the ingestion capability of InsureWave. Is that now part of your tool set? And tell us about why you bought that and then where it fits within your proposition now. Yeah.

14:06John Hele: So we did have an opportunity to acquire this business from InsureWave. When we were doing the work in Bermuda around kind of post-bind border row processing for the reinsurer, we understood that from a pricing point of view, 80 % of the information is very similar. So 80 % of the data was a lot of overlap. So we always knew we would most likely go to pricing from the post-bind order row processing. When this opportunity came up to acquire certain key assets of this business, including a client for pricing, it just gave us the other side of the coin, right? So to the two sides of the coin, pricing and then post-bind processing.

14:48John Hele: So for us, it was complimentary. And we are also intending to use the people and the technology and the assets in London to market and sell into Bermuda. We like being outside of the US when it comes to these markets from a data point of view. And it just makes a lot of sense since we have a lot of expertise in London around particularly commercial specialty, both the technology people, the AI people, as well as the data analysts who need to finish off what the models do, because there are no models in the world that are going to be 99.9 % accurate every single time. So there's a little bit of human element involved.

15:30John Hele: And the client in London, we deliver this as a service for pricing submissions. So when they get an output file, it is a finished product for them that many times will go straight through. I think the market is likely moving to tighter and tighter timing SLAs when it comes to pricing submissions because that's the real value. And that attracted me as well. It's fine to have expense savings or expense ratio impact, but for pricing, the timing SLAs really intrigued me because we think we can also improve upon what we're already doing for all clients in the London market. That's the strategic rationale behind the acquisition.

16:09John Hele: John, I don't know if you wanted to add anything to that.

16:12Greg Framke: No, it's a great opportunity. We got some talented people, as Greg said, and a happy client, which is always good. And we are improving and adding in new lines of business for them right now and also more functionality. So applying and fine-tuning the AI core routines to increase the accuracy.

16:36Robin Merttens: InnsTech All Sorts is back. After the popularity of our All Sorts event this summer, we're returning to the old library at Lloyd's on 20th October for another evening bringing the InnsTech community together. All Sorts is designed to be a little different from our usual events. There are no lengthy presentations. Instead, we'll have 45 minutes of market news, member updates, introductions and short pitches, followed by plenty of time to catch up with familiar faces and meet new ones from across the insurance ecosystem. and particularly relevant to this episode we'll be welcoming portage ai as one of the newest members of the insect community ceo greg framke will be joining us on stage to introduce portage and share more about the company with the network this event is open to insurers brokers mgas and insect corporate members with just 150 places available join us at lloyd's on 20th october register now at insect.co the industry particularly the soft market gets itself a bit tied up in saving money operational efficiency whereas i can't help thinking that the roi on most of this stuff is around quality of service speed of service better underwriting better decision making which is where the real value lies so you bought insure wave june it's now october give us a progress report how's the business doing got any clients anything you can talk to us about

18:01John Hele: Sure. I think given summer, everywhere, it's given us actually a reasonable amount of time to get ourselves organized. We are looking to kick off a delegated authority processing project, even as we're speaking now. Because of our experience in Bermuda, we've trained our models on this type of information, and we believe that we can bring the same level of accuracy and timeliness to the delegated authority processing that we're bringing to pricing. so we're kicking that off that's a really important project stay tuned we'll want to be talking about that very publicly as soon as we can but we've been organizing for that and in addition to that i'm very happy to say that we have hired a leader for our endeavor in london ben howell and we're very excited to have him on board and looking forward to working together how many have you got now total workforce we brought over 24 people split between It's equal parts technology, a smaller AI team, some data analysts who are really skilled in this product set, commercial specialty.

19:09John Hele: I really know the product well, some product people, and now Ben.

19:15Robin Merttens: John, in the 15 minutes since I've got to know you, I get the impression that you haven't come in to sort out the insurance industry's borderline processing problems, that you have a vision for AI that goes way beyond that. What do you see as the potential of this technology in terms of what it's going to do to the insurance industry?

19:36Greg Framke: Let me give an example. The game called Go. Go is one of the most complex games in the world. It's three-dimensional chess. And a few years ago, an AI-trained system was playing the world champion. And early in the game, it did a move that no one had seen before in that period of the game. It's called Move 37. and it took back the world champion. He had to think about it for 15 minutes before making his next move and the AI agent won and beat the world champion. And this move had been seen before but later in the game. No one had ever done it early in the game. In fact, when the computer played it, they thought it made a mistake and was going to lose.

20:20Greg Framke: And it did it because it could analyze years and years of all the games ever played and it thought, hey, what if we did this move here instead of there? And that's when you have your data and these predictive models can go through and analyze the data in much more detail than we've almost ever been able to do as humans. That can be a breakthrough. And when an insurer has their data well-organized with a good ontology and has all the data there, these tools, these predictive models can then be applied to that to help find that move 37 something that you may have missed for the positive or maybe the negative that price better maybe you could lower your price if this data was there then that you do that or you may stop doing something but actually we use mathematical tools that are over 100 years old the math has been around since the 50s and 60s and 70s, but the ability to collect the math is now here.

21:21Greg Framke: And I think it'd be one of the most exciting times ever in our industry. And that's what we want to help people with.

21:29Robin Merttens: I hear that. And I think I started a business at the dawn of the internet with my vision of how insurance was going to change. I was that fresh-faced, change-the-world disruptor. and then absolutely nothing happened for about 15 years. So my next question is, I could buy that vision and I get excited about it, but when's it going to happen? Is this going to happen in three years, five years, ten years, or is it going to be like invest in one of my businesses and wait 15 years before anything happens?

22:00Greg Framke: That's the question of the fourth industrial revolution. And what we've seen already is it's coming faster than the first, second, and third industrial revolutions. The changes happening are quite breathtaking. if you step back and think about it, where we were only five years ago or 10 years ago. And in industrial revolutions, it is a long time to have it widely used across the industry. But there are people who take advantage of it and who make it through the ups and downs. And there are always ups and downs. And we'll have one coming here and there, I'm sure. But the few that make it through totally transform the world.

22:39Greg Framke: And Amazon's Apple with phones, we didn't even think about a phone in 2000 when the internet was coming out. So all that has come together and it does accelerate. And in hindsight, it's fast. Sometimes it feels slow when you're going through it. But there will be some players, I think, in three years to five years' time that will be able to increase market share very profitably by applying these techniques. And that's who we plan to help.

23:08John Hele: I'm probably more optimistic about the timescale for something like this happening. It used to be there was a course of action that would get all your data organized first and then go get value from it. I don't think that's the course of action anymore. You can get good returns from doing structuring and extracting and organizing data the way we've been talking about. And I think those stand on their own two feet. I think there are means to this end, though. I think those are the means to the bigger picture end. And like John mentioned, we're already talking to a couple of companies who are already leapt to the end and are just looking for a way to get there.

23:50John Hele: So that's kind of the conversations we're having with a couple of clients, particularly in Bermuda.

23:55Robin Merttens: Just so that I'm clear and the audience is clear, you build this stuff. The world is jam-packed full of consultants and advisors who are standing up in in-stake events, telling everybody what it is they need to do. But a shortage of people are actually doing it in earnest. You're doing it. You're not telling people what they need to do.

24:12John Hele: No, we're doing this. We're bringing the solution in. We're working directly with a client. We support the models. We keep them from drifting. We integrate with other applications, which we prefer to do. We're not a platform player. We're not looking to replace your systems, but we want to be that engine that's receiving and feeding the applications it needs to apply. Now, we are also technology nimble, I guess is the best way to put it. So I think given our careers and our histories, particularly what's happening in AI right now, betting all your marbles on A technology is very difficult to do.

24:47John Hele: So we will license core AI models from really deep resourced company and then train those models on client data and then do everything that we've talked about. And that allows us a certain degree of freedom when it comes to advances in tech. And it also gives us a very deep bench to draw from without having to hire 300 people and try to bet that we know where this is all going. It's a good question. And just to be clear, these are our solutions and our products, and we're not consultants, certainly from that point of view.

25:22Robin Merttens: You can't do everything. Presumably, you use partners. Occasionally, I'm thinking particularly about integrations and other tasks. You'd want to focus on the areas where you're experts.

25:32John Hele: Yeah, we do and we can. We want to stay to what we're good at and what we're here to do. We've been in the game for a while. Where we need to bring our own partners, we have some really good partners that can round it out if need be.

25:46Robin Merttens: You mentioned funding earlier. You said you're well-funded. Did you have to go off and deal with some rapacious VC or PE?

25:53Greg Framke: Greg and I are funding it right now with the help of some close friends, but we're very well-funded. And we know all the VCs, basically, in the world. So at the appropriate time, we will go out and get more capital. But as I said, we're taking this very patiently. and we know this takes a long time. The sales cycles are long dealing with companies and we're here for the long haul.

26:12Robin Merttens: Look, I think it's fascinating. I think you've got a fascinating story. You bring a different approach. I really like the pricing model and the kind of roof before you're forced to buy. I think that's incredibly attractive. Speaking of somebody staring down the barrel of retirement, it's nice to speak to people who have real experience and still got the passion to go with it because there's nothing better and people who know how the world and industry and tech works and can bring both wisdom and that knowledge. I wish you the best of luck. We always give people on our podcast the chance to leave the audience with one pithy insight, the one thing you would like the audience to take away.

26:49Robin Merttens: Would you both like?

26:50Greg Framke: Let me go first. That AI is, as we said at the beginning, we believe is the biggest technology change of our lifetimes. It is the fourth industrial revolution. and companies and people need to start using it and get on it and really not just playing with it, but really thinking about how can this really help my business. It's much more than your co-pilot helping you sort through your mail. So I really encourage every listener to start really thinking about it, but demand value from the use of the tool. Greg?

27:20John Hele: I will just say that I foresee a day when we will be processing these kinds of complicated submissions in the time it took to record this podcast. So I would welcome a challenge from any potential clients, and we will put our capital where our mouth is. We will agree to do a project that can go into production only if it delivers value, period. That's what gets us up in the morning, and that's what we care about, delivering value. So take us up on it. I'm more than happy to engage in any complicated conversation folks would like to have.

27:55Robin Merttens: Well, that's a really good place to leave it. It's It's been a pleasure chatting with you both. You have become members of Insect almost immediately on starting your business. Thank you for trusting us and thank you for working with us. You are someone who is going to bring something for the industry to think about. We really look forward to working with you. Good luck. Any insurance companies out there, there's the challenge. Greg and John are ready to help you with your most difficult AI stuff. Hello, Insect, or either of them on LinkedIn. Nice to talk to you both and see you soon. Good luck with everything.

28:25John Hele: Thank you, Robin. Thank you very much, Robin. Really appreciate it. Thank you.

28:57Robin Merttens: network and be a part of the insurance intelligence for the curious.

From the publisher

AI experimentation is everywhere in insurance. But how much of it is actually making it into production and delivering measurable value? 

In this episode, Robin Merttens speaks with John Hele, Co-Founder and Executive Chairman, and Greg Framke, CEO and Co-Founder of Portage AI, about why they believe the biggest opportunity for AI lies not in automating the easy work, but in tackling some of insurance’s most complicated processing and data challenges. 

John and Greg bring experience from both sides of large-scale technology transformation. Before founding Portage AI, they worked together at Resolution Life on a major technology programme to establish independent operations following acquisitions in Australia, New Zealand and the US. The transformation involved around $400 million of investment and was designed to deliver annual savings of $150 million. That experience, alongside their work applying AI in production, helped shape their view of where the technology can create meaningful value today. 

Greg explains why Portage is deliberately targeting the difficult “last 20%” of processing: work that has historically been too complicated, expensive or technically challenging to automate. Rather than starting with the technology, their approach is to identify a specific problem, train models on a client’s own data and demonstrate value through a production-ready solution before asking the client to commit. 

The conversation explores one of the insurance industry’s longest-running challenges: turning fragmented, inconsistent data into something genuinely useful. In specialty insurance and reinsurance, information can arrive from brokers, clients and other parties in different formats and using different terminology. John explains how AI can help establish a common ontology across that information, potentially overcoming data cleansing and standardisation problems that insurers have spent years trying to solve. 

But better processing is only the starting point. Once detailed underwriting and claims information is structured and accessible, John and Greg believe insurers can begin applying predictive models to identify patterns that humans may struggle to find. John uses the example of “Move 37”, the unexpected move played by AlphaGo against world champion Lee Sedol, to illustrate the possibility: could AI uncover similarly unexpected insights in insurance data that lead to better pricing, risk selection and loss ratios? 

They also discuss where this is already being applied. Greg explains the opportunity in post-bind processing, bordereaux and delegated authority business, particularly across London, Bermuda and the US. He also discusses Portage AI’s acquisition of technology and people from Insurwave and how bringing together pricing submission processing with post-bind capabilities could ultimately make operational data more useful for underwriting decisions. 

The bigger ambition is not to replace insurers’ existing technology stacks. Instead, Greg describes an AI engine that can sit between systems, receiving and structuring information before feeding it into the applications that need it. With AI developing rapidly, he also explains why remaining technology-agnostic could matter, allowing different underlying models to be selected and trained depending on the problem being solved. 

Finally, John and Greg explain why they see AI as a much bigger change than another wave of process automation. John believes the industry is entering a fourth industrial revolution and that, within the next three to five years, some insurers will begin using these technologies to grow market share profitably. Their message to insurers is simple: move beyond experimenting with AI, apply it to meaningful business problems and demand demonstrable value from the technology. 

In this episode you’ll learn: 

  • Why John and Greg believe AI represents one of the biggest technology shifts of their careers 
  • What their experience delivering a major insurance technology transformation taught them about putting AI into production 
  • Why some of the greatest opportunities for AI could lie in the difficult “last 20%” of insurance processing 
  • How AI can help extract, harmonise and structure information from complex insurance datasets 
  • Why creating a common ontology could unlock more value from underwriting and claims data 
  • How better structured operational data could ultimately contribute to pricing, risk selection and loss ratio improvements 
  • Why specialty insurance, reinsurance, delegated authority and bordereaux processing are particularly interesting applications for AI 
  • How Portage AI approaches accuracy, explainability, security and human oversight when deploying models 
  • Why Greg believes AI should integrate with existing insurance technology rather than requiring insurers to replace their core platforms 
  • What AlphaGo’s famous “Move 37” can teach insurers about the potential for AI to uncover patterns and opportunities humans may have missed 
  • Why John believes the next three to five years could reveal which insurers are successfully turning AI into competitive advantage 
  • Why insurers should move beyond proofs of concept and demand measurable business value from AI 

If you like what you’re hearing, please leave us a review on whichever platform you use or contact Robin Merttens on LinkedIn. 

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