Scouting for Growth
00:04:44 · Sabine VanderLinden, Richard Gunn
[00:04:44] S0: Yeah, it's interesting when you say there are very few people liking technology and insurance. I hope you will include me as one, as well as Nigel Walsh, because we have been in the industry for quite a while, right? [00:04:57] S1: Absolutely. Mister and missus in short tech. So... [00:05:03] S0: But, you know, when I think about Hyperexponential, and I know I reached out to you many years back because I was really fascinated by what you were doing there. And when you think about decision intelligence is an area I dove into many years back when I was working with FICO and Pega as well. So first, what does ep exponential mean for you, for the team? And tell us a little bit more about Hx and Hx Renew as well so that we have a little bit of a context around the company and what you are doing for our industry.
00:05:39 · Richard Gunn
[00:05:39] S1: Yeah. So there's a number of questions in that. So what are we what does it mean? What are we trying to build? So trying to build the analytical backbone of the insurance sector, looking at it through the lens of pricing, right? In terms of like where we operate and what we focus on, we kind of... The verbiage we use is we're enabling our clients to achieve pricing decision intelligence. And you mentioned you got kind of experience in that in that field, but what I'd really resolve that to is just creating, a tight iterative feedback loop between, like, data decisions and outcomes. And so we're very focused in the context of pricing around how we can enable clients to achieve that, and that was a motivation for why we built Hx Renew. So Hx Renew is platform. It's very much a platform. So, like, a a key a key part of our offering is that we enable the actuaries in insurance, reinsurance, MGAs in the market themselves to build, deploy, and iterate on those on those pricing models themselves. So that's in terms of, like, what we do. Like, why we're here? It's probably a slightly different question. That'll be more, like, akin to looking at our values and and the kind of culture that we're trying to build. Like, ultimately, we look to hire people who are very passionate about this space, who are very invested in learning, and then we all kind of combine on the same problem to try and, like, actually kind of, like, further this part of of pricing as much as possible.
00:07:01 · Sabine VanderLinden, Richard Gunn
[00:07:01] S0: That's cool. And so I heard you had Hx live recently. How did that go? Tell us about the conference. I assume you are going to do this every single year now. [00:07:13] S1: Yeah. So it started... So last year, we did a summer party, which was like dip your toe in the water. We figured people would at least turn up if they knew that there's alcohol there. And then this year, we built up the courage to do HxLive, which is predominantly customers and some partners, like a celebration of what we've achieved, a few customer panels and so on and so forth, but also sharing a little bit more around our vision and what the what is the next year, what's the next two years gonna look like. So we were, yeah, in inundated with with applications. We were actually oversubscribed, which was great. I think we had over 250 people there for the day and more people for the evening. Apparently, we had gate crashers, which is good. Interesting. It... It's definitely something we'll be doing each year. And in fact, we've... I'm recording this from from New York. We just opened our New York office, and we've got plans to start with a user group in New York as well with some of our clients over this side of the pond. And then I expect that's something we'll run kind of multi threaded. We'll have a New York Hx live as well as a London one.
00:08:10 · Sabine VanderLinden
[00:08:10] S0: That's super cool. I can't wait to maybe come to one of them in the future. So let's dive into, you know, advanced pricing decision intelligence. You know, what does that mean? You know, what are the crucial components we need to think about when we think about insurance and the insurance business, pricing, underwriting, actuaries, you know, how do they improve their day to day work in the world of artificial intelligence? And so how do you help them improve their decision making process?
00:08:43 · Richard Gunn
[00:08:43] S1: Yeah, good question. So there's lots of steps that go into kind of pricing and underwriting that we think about either how we do it or how we integrate with other providers, other parts of the workflow to achieve that all the way from initial submission, data triaging, predictive modeling through to kind of like the risk assessment and manual underwriting adjustments through to like quote and bind and so on and so forth. Probably the kind of cleanest way to illustrate how we're trying to move the industry or at least enable our clients to go from a to b is to kind of like give a couple of examples. And I would say, like, the main part of our thesis is that, like, historically, much of the insurance industry have looked at, like, risks on an incidental basis, particularly, like, five, ten years ago, or for many insurers still today, if they're pricing a risk in Excel, they'll kind of bring that information in. They might bring in some basic information to create a technical price, then they'll throw it away again, Or they might run some rate adequacy at a periodic basis and surface it up in one way or another, but they're not kind of really, like, capturing that data and an additional data to kind of make better decisions over time. Like, a good example might be if you're an underwriter and you get a submission from a broker, like, one underwriter just sees that submission. It kind of, like, leverages their brainpower to remember the last four or five and thinks about how they can approach the conversation with the broker most effectively. Whereas we would hope that an underwriter in our platform will also be exposed maybe information around the last five or 10 submissions from that broker and actually maybe what you priced them and like how they responded to that and maybe to show you some benchmarks from other brokers who are submitting your information for certain risks so that you can then leverage that in the conversation and your dialogue with with that broker. So it's about just kind of putting more information in the hands of, in that instance, the underwriter so they can hopefully definitely make a better informed decision, and hopefully over time that will aggregate towards them making better, more profitable decisions.
00:10:35 · Sabine VanderLinden
[00:10:35] S0: Yeah. You know, as you are talking about technical pricings, I remember when I was working with actually a company called SSV, those spreadsheet, those technical pricing spreadsheets that actually reviewed to actually see how we could improve things. And for me, it was very static. I said, you know, how can we just look at spreadsheet to make decisions? And I hope today in the time of artificial intelligence and platform, as human hx Renew, we can remove those spreadsheets and actually start doing much more dynamic pricing and being really able to customize those pricing for our customers. Am I right? Are we going there, Richard?