Scouting for Growth
00:16:43 · Sabine VanderLinden, Richard Gunn
[00:16:43] S0: Well, I'm thinking maybe a title, a new title for this discussion, the pricing nerds. But we'll see. We will see what would be the best title for this. But so when we look at some of the amazing case study, and I was playing and checking your website, I saw you have Aviva, Convex, a new case study which probably came out like five days ago with ages. Tell us about what you've done with some of your customers, some of the big brands you're working with, and share some of the value you have created for them, because some of the numbers are quite impressive, I've seen. [00:17:16] S1: Yeah. I think this is... I think Aviva and Aegis might be a great example of how competitive the insurance market really is. Yeah. Actually, at HxLive, we had a couple of CEOs on stage from some of our respective clients. I won't name them, and they ended up having a competition about who had the best team of actuaries, which was quite quite entertaining. So and likewise with Eva they were able to build 20 models in their first I think nine or ten months. [00:17:42] S0: Nine months, yeah.
00:17:43 · Richard Gunn
[00:17:43] S1: 58 models in their first nine months. I do suspect there was a bit of a bit of competition there. I would say that all not all models are equal, right? And so take from that what you will. I like really kind of like core to how we've approached this problem is this again might not be very popular. Like Excel was very good in many ways. One way is that it kinda, like, combines, like, the three core parts of, like, software development into a nontechnical user. Like, you can, like, define what you want it to look like by merging cells and this, that, and the other. You can define your data schema. In fact, you don't have to. It just defines your data schema for you, and you can write the algorithm that sits between the two, and you can either do that within a cell or you can jump into VS Code and have a bit of fun with it. And what we've found and what the founders found when they were kind of decided to set up Hyperexponential is that in the kind of yesteryear, in that way, if an underwriter wants to make a change to a model, they can just sit down with their actuary and make that change live. And as we kinda, like, move towards kind of modern tech capabilities, it actually broke down that kind of feedback loop between actuaries and underwriters. And, like, found themselves in a position that if an actuary wanted to make a change, they'd have to either go through IT, they'd go through a third party vendor. It would take them, like, days or weeks or months rather than be able to do it really quickly with their underwriter. And so, like, central to our proposition is really just putting it back in the hands of the business, like actuaries and underwriters to kind of, like, self serve, if you will, would be the kind of, like, technological speak or the tech... Technology company speak. And therefore, you kind of take us out of the loop. So we try and put all of our might into making it easier to use our platform so that you don't actually need us. But if you're reaching out to us and our team of consultants, it's because you want to understand, like, what's this new best practice or this new capability? How could I leverage AI in Hx Renew, for example? And not so much like, actually, how do I, you know, run rate change or how do I update a parameter or something like that? So... Yeah. From... Sorry.
00:19:37 · Sabine VanderLinden
[00:19:37] S0: Yeah. No. I think this is fascinating because I'm hearing that, you know, as we spend... I mean, I spent a lot of time talking about artificial intelligence, you know, over the past few months, but you actually made a very important point that we are moving the skill set of using those capability to the business audience, the underwriter, the actuaries. Right? We still need our IT, but actually we are shrinking those teams, eliminating redundancy in processing, and then seeing the ability to deliver on very specific business outcome by enabling that business user. And I think it is very important to understand that. Right? Everybody can work together. But at the end of the day, the decision makers able to make the money already the risk for the business are empowered to actually use those tools.
00:20:21 · Richard Gunn
[00:20:21] S1: Yeah. No. Absolutely. So I guess to come back to a question, like, what's some of the Like, Aviva were able to, like, cut the time that it took them to build a new model by about 75%. So that's, like, critical if they wanna bring a new line of business to market. Like, the quicker they can get that out there, the better. Kind of already mentioned the kind of cadence at which they're able to release them. But importantly as well, like on the Aviva side, they were able to get the kind of new policy creation, like cut down from like an hour to like five or ten minutes. So again, what that resolves to is, like, doesn't mean that you need less underwriters or less actuaries. It means that the time they have, they're spending on higher value activities. And that might either be like an actual like risk assessment or it might actually be more on the entrepreneurial side. It's like, okay, I theoretically have more time. I could either do more of what I was doing and therefore be more productive and more valuable, or I can start to experiment around like what other data could I bring in? What other insight could I bring in at point of pricing that's gonna enable me to make a better decision? So kinda like really enabling... Like, different clients will take that in different directions, and also, like, macro trends will drive whether or not they're, like, just looking to optimize their expense ratio or whether they're looking for, like, loss ratio gains. But, like, the software shouldn't be dictating that.
00:21:30 · Sabine VanderLinden
[00:21:30] S0: Yeah. You know, earlier you mentioned, you know, when we are talking about big data, you actually talked about external data sources. So I would love for you to actually help us understand how do we work with Hx Renew when we think about integration and connectivity. You know, I assume you have built an ecosystem of partners to actually get access to external data sources while working internally with the underwriters, the actuaries, the pricing team to leverage the internal data. Can you tell us more how you actually leverage your tools and techniques to actually get for sure, improve the process and drive this efficiency, but also mentioned competitive advantage, drive that competitive advantage through data and partnership.
00:22:12 · Richard Gunn
[00:22:12] S1: Yeah. I think you summarized that better than I could, probably. So I think one thing that's kind of fundamental to our platform is we enable our clients to be able to build those integrations themselves if they wish and if they want, and that is critical. Again, like, it goes back to, like, reducing or getting rid of any dependency you might have on on the software provider. Nonetheless, like, we have the luxury of being able to scan across both the broader market, but also our 35 to 40 or so clients and see like which integrations, whether that's with like systems providers, whether that's policy admin systems, data ingestion tools, so on and so forth, or whether that's with like third party data providers and see like which integrations are our clients doing time and time again. And therefore, we should look to kinda, like, proactively help them and accelerate that. So you're right. We have a ecosystem called HxConnect. We have, like, a whole host of integrations there from systems all the way through to data. And then, actually, what's really important is, like, how we then build a relationship and partner with our clients so they know which ones to use. And, like, someone shared me an interesting article. It was related to the impact of AI in enterprise, but it could be the impact of technology and enterprise. And it kind of resolved it to the fact that, like, 10% would be the underlying technology or either kind of LLMs and and for Gen AI. 20% would be the applications that you build on top of it, and, like, 70 would be the change management. That's how, like, it would broadly resolve to the impact that you might have in the enterprise space. And I think that's super powerful. Like, we built a really flexible platform which clients can self serve. That means they can use it brilliantly. They can also use it poorly. Right? And so, like, it's incumbent on us, and this has been a key learning for us over the last, like, six or seven years as a company is actually, like, the onboarding, the customer success teams, the best practices that we share, the user groups, HxLive, they're all really, really important component parts of setting our clients up to succeed. Otherwise, you can kind of...