Scouting for Growth
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?
00:11:12 · Richard Gunn, Sabine VanderLinden
[00:11:12] S1: Yeah. I mean I mean, we have to. Right? If we think about, like, if you just take a step back, like, the landscape of risks are revolving. Like, what we are insuring now is materially different to what we insured in the past. So it's important, like, the pricing capabilities kind of keep up with that. Even if you look at, the FTSE one hundred or the Nasdaq, like, ten, twenty years ago, a lot of the assets that are baked into the company valuations there would have been, like, bricks and mortar. There'd have been, like, hotel chains and so on and so forth. And now we ensure an underwrite risk with relation to Airbnb, which is, like, almost all intangible assets. So, like, it's necessary that our pricing capabilities evolve with the risks that that that we're writing. And, like, cyber being, like, the poster child of this and particularly with, like, the recent challenges around CrowdStrike and so on and so forth, like, you need to ensure that you've got a pricing environment which allows your underwriters to kind of react to that kind of emerging data rather than, you know, historically maybe updating inflation adjustments on a, you know, six monthly basis and not much more. [00:12:09] S0: Yeah. And so when we look at what you guys are doing at Hyperexponential, tell us a bit more about big data and analytics and how you actually help provide that accuracy and help your customer drive profitability. At the end of the day, we all want to make more money, right?
00:12:29 · Richard Gunn
[00:12:29] S1: Yeah, we do. Whether you're in insurance or not. Correct. As CRO, broadly my responsibility is to at least manage one side of that P and L and consider the other side. I I I think probably one thing I'd say, and this might be less buzzy, but actually, we do less with the big data side of things, particularly in, the specialty commercial, more so, like, our clients are starting to use us in the SME space. So the full gambit of commercial P and C as there's there's some larger data sets there. But, like, actually, we often find that we're enabling our clients to work with, like, the small, sparse, fragmented data sets. And, like, how do you wrangle, like, insight from that data, and how do you use that to give you a competitive edge? And, like, really, like, the... One of the, like, core value props of our platform, if you will, but often it takes, like, a while for our customers to really, like, appreciate the value of this is no matter what our clients do on our platform, what pricing models they build, etcetera, what actions and activities the underwriters take will capture all of that data. So it accrues to an, like, evolving data asset, which could be coined, I guess, big data, which you can then start to evaluate and analyze and pull out trends. So I think that's just one distinction I would make is actually, like, central to our thesis is that, you know, it's gonna become table stakes that you're capturing, like, certain data points as you price. And if you don't have that, whether it's benchmarking or third party data that's available to most of your competitors, then you will like drop behind. But if that's like assumed, then it's like, where are you gonna drive your competitive edge, you can drive your competitive advantage? And that's where we're very focused on. Like, how can we make it as effortless as possible for different insurers to say, like, actually, we think this exposure method is going to be, like, interesting for us and enable us to, like, unlock some more value and more profitability in the market and just enable them to kind of bring that in and expose it to their to their underwriters.
00:14:19 · Sabine VanderLinden
[00:14:19] S0: So as I listened to you, Richard, there are two questions which come to mind. First, I just want to clarify, you know, do you do every type of insurance? Or you just mentioned cyber, SME. You know, let's clarify maybe the lines of business that Hyperexponential is focusing on. And the second question for me is, as you're actually looking at your customer base, you know, how do you, you know, who do you actually want to talk to in those organizations?
00:14:49 · Richard Gunn, Sabine VanderLinden
[00:14:49] S1: Yeah. Good good question. So I would say, like, we mostly work in the commercial p and c space all the way through from specialty to kind of SME. We're being pulled in a couple of other directions by some of our clients, like, particularly if there's, like, heavily heavily broke to, like, corporate health or group health, for example. Got some clients using us in that area. And there's... Even some of the kind of personal lines are quite heavily broke when you kind of subsegment it, but but that's where we kinda, like, focused. Our founders started in the Lloyd's and London market. We know that place very well. We built a platform, which is very kind of fitting to that. In terms of who we like to speak to, it can depend on the organization. I would say, like, in our early years, we would typically start by speaking with the actuarial team, and that's still where we find we have, like, the initial quick wins. Like, our platform, amongst kind of some of other items that I've kind of discussed, it enables actuaries to be able to build and deploy models leveraging open source programming languages, like notably Python. And so that's really... That we generally find that there's a there's a big appetite for clients to use our platform because it means the individual actuary gets to learn and upskill on how they use on how they use Python. Sorry. I've got someone knocking on the door here, and I I don't think it's priority, so... [00:16:02] S0: No problem.
00:16:02 · Sabine VanderLinden, Richard Gunn
[00:16:02] S0: No problem. [00:16:04] S1: And but then increasingly, like the value actually derives often to underwriting IT as well, if historically they've had the IT teams build a platform, and then also to kind of leadership. Leadership increasingly is saying like, how can I leverage what's happening at the kind of the coalface to kind of help me take more of a portfolio steering approach? And so, like increasingly, we'll have conversations with underwriters, IT, the exec team, or on the actuarial side, just anything related to pricing. We're basically pricing nerds. We love pricing. So if someone wants to talk about that, then then we'll be kind of a willing audience. [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.