Scouting for Growth
00:03:04 · Sabine VanderLinden, Sabine VanderLinden, Bastiaan de Goei
[00:03:04] S1: he said this, if the most targeted organization on [00:03:07] S0: the planet can do it, then an insurance company should be able to do so too. A little of Las Vegas come through in the audio. I make no apology for that. This is what life means. Here's my conversation with Bastiaan de Goei from OpenAI. [00:03:29] S1: Hi, Bastiaan. Hi, Sabine. Thank you so much for joining me today. [00:03:33] S2: It's my pleasure. Thank you so much for having me today. [00:03:35] S1: So, Bast, I'd love to go into who is Bast because you have an amazing background from Europe to The United States, and I would love our viewers and listeners to know you a little bit more.
00:03:48 · Bastiaan de Goei
[00:03:48] S2: Well, thank you so much for the kind words. I hope I can live up to them. So my name is Bast. Maybe that for your listeners already tells a little bit about my background. I'm Dutch by origin. I lived for a long time in The UK where I actually found my way into insurance, worked for AXA Group and had the incredible pleasure to work in different parts of the group, in retail insurance, wealth management, banking even, life insurance, specialty insurance. That's the advantage of an incredible, organization like AXA. And at some point, the group found itself in a need to go to the next stage, what they called their next phase or AXA Next. And it was in that context that I also relocated to San Francisco in order to help lead the group's transformation. This partnerships with technology companies such as Facebook or Meta nowadays of course, where the group was one of the first companies to sell insurance policies via Facebook Messenger. Just super exciting. This is now ten, twelve years ago. And during that time, I found myself being in need by startups and technology companies who were actually looking to understand the insurance industry. So they needed a bridge of somebody who understood insurance, but also understood technology. And as a result, I made a transfer to join an exciting startup company, which was Instabase. I spent quite a bit of time with them, then worked with some other fintech companies. And today I find myself leading financial services marketing for OpenAI.
00:05:22 · Sabine VanderLinden
[00:05:22] S1: Wow. Congratulations. You have been in this innovation space leading amazing projects and helping actually, like IAM, move corporations from highlight to execution. Right? Right. So when you look at the larger organization like AXA, for example, you know, 30 old, core system potentially, or maybe more, you know, updated, how do you bring your knowledge from working with big hires into that new world of open AI? You know, how does that look like and how you start solving big problems?
00:05:59 · Bastiaan de Goei
[00:05:59] S2: I love that question. And I think that there are, two specific elements to it. And I think the first one, is rooted in understanding and trust. So one of the first things that you need to nail or really get done is you need to start talking, get into a real conversation. That conversation needs to be built on understanding and trust. So when you are talking about complex large language models, OpenAI's recent Astra models and or like persistent agents, the first thing that needs doing is to translate those incredible capabilities in something that is real for an insurer. And so, okay, there is something that is a persistent agent. What does that mean for an underwriting workflow? And so like truly illustrating that is step one, cause that earns you the conversation and earns you the trust to say, okay, this is a technology company, but they have an understanding of what I experience as an insurance professional. Now the second step is to help guide and work together with large companies like large carriers to actually make that real. And so many times what I find is that I actually have to temper enthusiasm Because as soon as people have an understanding, okay, now I understand that what this could mean for me as an organization, the natural inclination is to then want to do everything all at once. And that is actually the wrong instincts. What I found is that it is much better to basically achieve efficiency by a thousand cuts. And which means start small and add rapidly additional aspects of automation and efficiency to them. And we can work together in a partnership to help make that real.
00:07:48 · Sabine VanderLinden
[00:07:48] S1: So I want to start diving into what you just said. Right? What is already real, right? The intelligence layer. And what we want to do is move that intelligence layer into production. We heard about the numbers, too many pilots, not enough execution. And we are here at ITC Vegas to actually drive, you know, that operational execution. So everyone at this show has seen the demo. I mean, we have a lot of demos, right, downstairs here. And where is AI generally load be real inside carriers today? So that is the first part of my question. Doing the work that would break something if you switch it off tomorrow.
00:08:32 · Bastiaan de Goei
[00:08:32] S2: Right. So I think that's a super fair question, and this is one of the things that I would ask as well when I'm a a buyer. So like where... That sounds great. Where does this already work? Where are you achieving results? And can I talk to those folks? So we are very lucky to work with some of the largest carriers in the world. Some of the public examples that I can share are for Travelers, for example, which is obviously a major insurance carrier and we are lucky enough to have worked with them and still work with them on their claims operations. And so this is a company that obviously has been in the market for a really long time. Very reputable business. It needs to be correct and precise. Right? Insurance, relations, they are all based on trust at the end of a day. And the moment of truth is the claim. That is that insurance is this magical industry where you spend a lot of money for a long period of time and you don't actually know whether it actually lives up to something and this comes real at the time of claim. So what we did together with Travelers was to make the claim process intake, intake process much, much easier. And so today, within OpenAI powered Travelers solution, 80 to 90 of data that as part of the claims intake process is fully done with the AI powered tool done by Travelers. So that's a real tangible example where a lot of these automation and double check and all of that is all done automatically. Another example from a, a different, business line, health insurance, if we take Oscar Health for example, they found that their particular friction point was not on the intake, but it was on the double checking and the actual verification of the claims. And so their analysts and claims adjusters were spending a lot of time looking at all of the different data and verifying that those were correct. And so we developed, co developed a solution with them in order to accelerate that process. And in this case, we were able to accelerate that by 50%. And so that means that every single adjuster just had like 50% more capability, capacity to process claims, which at the end of the day meant that the experience for the end customer was much faster and therefore more satisfactory.