Scouting for Growth
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.
00:10:59 · Sabine VanderLinden
[00:10:59] S1: So looking at both of these examples, you know, what could we say is common when you start looking at your experiences working amongst and with a lot of carriers? So that would be the first part of my question. I suspect you you see some patterns. And and some of the conversation I'm having here at the conferences, how do we move maybe from one siloed workflow to looking at end to end workflows and starting compounding the results we see from our execution?
00:11:29 · Bastiaan de Goei
[00:11:29] S2: Yep. Great question. I think that this actually applies to transformation generally. It is not even specific to insurance. So we've seen actually a lot of companies across, our entire customer base who are actually really good at optimizing a specific step in a workflow that could be data intake, it could be data validation and verification, two examples that we just talked about, could be follow-up, these types of things that are practical, but they're also isolated. And so when we are, as humans, thinking about an end to end process, we are thinking about all of these different steps in one single flow. And that is earlier today, I spoke with a gentleman who said, is this the new straight through processing? And I said, well, you could think about it that way. And why I'm so incredibly excited about the latest technologies and developments is that powerful frontier models like Astra, they are able to stay persistent on their task and see it through end to end. And so rather than taking one system and one process, it is able to understand that for the next step in that process, needs to consult with another system and with another system all the way pushing this towards the end. So if we are talking about a underwriting process, for example, in commercial underwriting, underwriters receive submissions from brokers consisting out of like different data packages, loss runs and broker presentations and things like that. And they obtain these manually, they review them and the end result is that up to, you know, 50% sometimes of these submissions are being ignored because the underwriter is simply inundated by submissions and basically ignores the rest. And so with persistent agents, like Astra, you are able to actually do like a lot of those flows so that it picks up the submissions from the email system. It's able to find and see the data in those. It's able to consult with a pricing engine and to actually get this priced. It can balance this with your portfolio and see if there is... This risk is accretive or not. And subsequently use your company's templates to actually prepare a proposal for this end customer. And so here you are touching like four or five different systems in order to get to the end result of a actual quotation. I think that is what we are talking about when we are thinking about all complete processes.
00:13:55 · Bastiaan de Goei, Sabine VanderLinden
I think that it's only now with the latest frontier models that you're able to really do that. [00:14:01] S1: So let's talk about Astra, Frontier Model. And you actually highlighted a scenario where Astra will go and talk, touch different systems. So to actually automate and hopefully augment the human, how do you see that relationship between human, human judgment, trust and governance, whilst we are now orchestrating processes which are managed by an astronaut?
00:14:28 · Bastiaan de Goei
[00:14:28] S2: Yeah. I actually love the use of the term orchestration that you just said. So I think that this is very much the way that I envision how not just underwriters, but anyone who is like in charge of like an important workflow would see their daily job. So I myself, when I'm looking at how I conduct my work, I obviously have my own workflows and I work together. So earlier this week we released Dots, OpenAI's version of Persistent Agents. Two days ago, I was for the first time that I did not touch or open a single application surface. I did not open my Gmail. I did not respond to my Slack messages. I did not open up a Google Sheet or a presentation, software. Instead, I was only engaging with my agent and the agent was responding for me on Slack, was preparing presentations, was preparing notes and did all of this on my behalf. And I was literally just orchestrating and validating that what it was doing was correct and asked for adjustments where necessary. And so it's a completely new way of working. Now if you apply that to that same insurance underwriting workflows, you become essentially an orchestrator of the underwriting process rather than the operator of one. And I think that that can dramatically expand the capacity of an underwriter and the way to stay in control of that, which is super important. At the end of the day, the underwriter needs to stay in control, is that, the agent can get this to a position where it is fully priced based on a series of assumptions and have a ready to go quotation and for the underwriter to subsequently say yes or no. And it can even identify higher risk to lower risk type of submission to say like, Hey, here I'm extremely uncertain. Here is something that I'm a lot more certain about. And so ultimately I see that you will have portfolios at the end of the day of quotations that are all ready to go. And so you can focus your attention as an underwriter on those that the agent was least sure of.
00:16:39 · Sabine VanderLinden
[00:16:39] S1: So let's visualize that. So I'm Bast, and I have my chatbot on my browser, but that is a space I'm working from, connected to Slack, Gmails, and everything is happening in front of me. So if you actually look at this claim, chief claim officer or this underwriting manager, right, and all are AI enabled today, describe for us properly, you know, because most people will hear things in a different ways, right? Picturing it is going to help us understand really what we see on the screen. What does that underwriter or that claims officer, what do they see when they arrive at their desk at 09:00 in the morning and open that beautiful browser?