Scouting for Growth
00:20:10 · Amrit Santhirasenan
And that includes some of the big ones now, the likes of Guidewire as well as the smaller data providers. And the other thing that we're super excited to do is speak to clients, right? One of the most important things you can do as a provider of technology is listen to your clients' problems. They're changing very quickly. You know, AI is transforming the way some of those data silos are being attacked. You know, people are often talking about data AI in respect of data ingestion, but it's also solving the data mapping, the data flow problem. We're applying that very deeply inside Hx right now to make our clients' data silo, to break some of those data silos. So super interested to hear the challenges that our clients are facing. Ultimately, we build infrastructure, right? That's what we do. We don't build pricing models. Our clients build models on top of our infrastructure. So hearing about the challenges that we, our clients, are facing when they build those tools or how we best build the right infrastructure for them. So those are the two key themes, lots of new challenges from clients and also meeting new providers.
00:21:15 · Sabine VanderLinden
[00:21:15] S0: So one thing we need to highlight as we are discussing here, Amrit, is you have amazing clients in The United Kingdom and some of those clients are also working with you in United States. So, you know, when I go into your website, I see Aviva, Conduit Re, Aegis London, SGI, among so many others you are working with. And The UK is different from The United States. So can you explain how you are addressing those differences, taking advantage of the 35 or 45,000,000,000 of GWP already transacting and bringing the really best of change to The United States, is highly regal... Regulated and state based regulated. Tell us a bit more about that.
00:22:00 · Amrit Santhirasenan
[00:22:00] S1: Yeah. Fantastic questions. These are really, really great questions. So I'd say, yeah, 45,000,000,000 and counting. Hopefully, it'd be close to double that in the next couple of years. So, you know, the $100,000,000,000 mark is the one that's super exciting for us. 100,000,000,000 is not a small number. So what would we say here? One of the beautiful things about insurance and probably one of the formative kind of learning proving grounds for us early on is that insurance companies are multinational very, very early, Right? Because insurance companies, you know, the benefits of diversification in an industry make insurance companies naturally want to be big, they become geographically diverse quickly. And so while it's true, we're a British company and that we've got some of the world's leading insurers in Britain on our platform, on our website. We've got some of the biggest insurers in America on our platform too. The marketing restrictions about talking about them is a little bit harder for us, but most people know who they are. You know, some of the world's biggest insurers anywhere are headquartered in The US, and many of them use our platform. More than 30% of our revenue comes from America already. You know, one of our clients has more than $5,000,000,000 of premium and two and a half thousand users pricing and rating risk on our platform every day all across North America. And what that allows us to do is to really see the differences between how things are done inside a company that underwrites both European and British risk and North American risk. And that's been a huge benefit for us because we're able to see actually the kind of different ways they go about it, how important the admitted side of the business is, actually the difference with respect to pricing and rating. Actually, how much latitude you have to flex your rates is very, very different in North America compared to how much latitude you have to flex them in The UK. And that influences how we design the models with our clients. It influences the investments we make in the post bind process, the post analysis process with respect to filing of rates, and also the effort and energy that needs to be put into for explaining why a price is what it is. Beauty of building a platform like ours is because it's extremely general.
00:24:17 · Amrit Santhirasenan
It can be used to solve all these different challenges at once as part of the process. In The UK, we tend to bundle up clearance, triage, rating, pricing, filing maybe less the filing side we don't do that but like post bind administration, bind execution. We lump all of these things together in pricing. I've seen in The US, these are like very different parts of a workflow. And we're really investing at the moment at speed, again, having the benefit of the investor base, the experience base that we do with Marcus Ryu from Battery and Angela Strange from Andreessen Horowitz. We're really focusing a lot at the moment on building out that richness of componentry that's much more tailored to The US specific challenges that I outlined there. They're coming thick and fast. Many of our clients are doing it already and there's much, much more product work that we're doing here. Our leader of product, so the intersection of business challenge and technology, is based in New York. So we've got a lot of American expertise, it's only growing in the business already.
00:25:19 · Sabine VanderLinden
[00:25:19] S0: So much looking forward to meeting the team at the conference. And lovely to hear that you also spend a lot of time with Angela Strange. We admire Angela at ACE Extreme. And, you know, followed her and listened to a lot of talks because she's the one which who actually went into INSURTECH and observed our market as well, which I'm sure she will love this question I'm going to ask of you is we talk a lot about artificial intelligence and we know we are going to talk about AI a lot at ITC. Vegas and I'm sure a lot of the attendees, whether they are partners or insurers, chief underwriters, actuaries will want to ask you that question. How do we ensure that we use AI in a trustworthy, responsible, and ethical way when we look at all the development we are seeing in general... With generative AI?
00:26:13 · Amrit Santhirasenan
[00:26:13] S1: Yeah. It's a great question. It's a super hard question to answer. I'm really optimistic about this. Insurance is a huge judgment based game. Right? If you want to look at it through a game theoretic or or a game structured lens, there's a huge amount of judgment there that factors it. Even in the risks that are much very homogenized, very straight through algorithmically driven, judgment in selection of final rates is a really, really key thing to do. And I think one of the things that people are probably ignoring a little bit in the AI space is it's wonderful for productivity, right? It's been an amazing thing. Like most scientific and technical revolutions do, a huge driver in productivity. You know, the idea that you can ask a robot to ingest unstructured PowerPoint, photo spreadsheet. This was like complete magic even two years ago. Right? And now it's part of the course. People are frustrated if it's not 99% accurate. The idea that it's anything more than 10% accurate isn't mind blowing anymore. That's the technology for you. But I think there's two things. Think one of the other sides of AI is how it provides a framework for reasoning. The idea that you could ask a model, say, tell me why this risk you think this risk is a good thing, and it will play something play its rationale through. You could ask an AI based LLM, say, like, I'm gonna give you some information about this risk. I'm gonna give you some features about it. Can you tell me why you think this risk is good or bad? And actually, I think what we're gonna find is like, mechanisms by which we can enrich our own judgment and decision making through interaction with models is something I'm really excited about. I think you need a framework to reason about risk. You need to build a framework for operationalizing that reasoning. I'm a bit biased. I think we have the best one out there. And so we're very excited about this. With respect to the question about how we can make sure, look, I think there's a huge amount of work that needs to be done in alignment and safety and insurance specifically. I think insurance is a is a very specific kind of field of AI where actually... Sorry. AI applied to insurance is a very specific field that needs its own dedicated attention. I think insurance companies could come together. I think they should be working with technology providers.