InsTech - insurance & innovation
00:02:35 · Matthew Grant, Richard Gunn
[00:02:35] S1: You've been with the company seven years. You went to the eighth birthday party, so you joined one year into the company. How big was HX then when you joined? [00:02:42] S2: So I think I was the fifth person to join HX. I was the first non engineering hire. So broadly, my role was to work alongside the founders. So was there as we were working out kind of what product market fit looked like, I guess, and how to sell it. One of my kind of early kind of projects, if you will, at HX was to apply for the Lloyd's Lab back in the day and to take us through that program. And then, yeah, since then, we were able to find partner market fit and sell to a few customers, and my role has kind of evolved as as a result of that. [00:03:16] S1: How many people today in the company? [00:03:18] S2: 220 something, two twenty one, I think, the last count. Yeah. [00:03:23] S1: It's a lot of change, as you said, seven years, and we'll talk a little bit about your own personal experience, but you're heading up the US operation out there now. I think last time we spoke, you had 20 people out there in The US on the ground. Obviously, a big market for you.
00:03:23 · Matthew Grant, Richard Gunn
[00:03:23] S1: It's a lot of change, as you said, seven years, and we'll talk a little bit about your own personal experience, but you're heading up the US operation out there now. I think last time we spoke, you had 20 people out there in The US on the ground. Obviously, a big market for you. [00:03:35] S2: Yeah. That's right. So I moved over here a year ago and started building out a US team. Two of the hardest things to get right when you expand into a new geography. One is to get the culture right, and two is to win your first customer. Immersively, we had a little bit of an unfair advantage on winning your first customer because we were able to sell to some large US carriers from The UK, particularly through COVID, kind of decreased the geographical kind of barrier there. And I moved over to start building out a US pod, start building out a US team. And, yeah, over the last twelve months, I've scaled up to about 20 people. They are continuing to hire, which is exciting and exhausting. But, yeah, I'm based over here, based down in Brooklyn and New York. [00:04:15] S1: We'll come back to the experience of moving to The US and compare and contrast to The UK. But we should just baseline it. Hyperexponential HX was initially known as a pricing platform. I know you've expanded a bit since then, so how do you describe yourself in terms of what problem are you solving for your clients today?
00:04:15 · Matthew Grant, Richard Gunn
[00:04:15] S1: We'll come back to the experience of moving to The US and compare and contrast to The UK. But we should just baseline it. Hyperexponential HX was initially known as a pricing platform. I know you've expanded a bit since then, so how do you describe yourself in terms of what problem are you solving for your clients today? [00:04:32] S2: Yeah, sure. So, you're right. We are kind of most commonly known for our pricing and rating capabilities. Our mission has always remained consistent over the last eight years. Lots of things have changed, but our mission hasn't, which is to build the decision infrastructure for the insurance ecosystem. And that started with majoring on pricing and rating. In terms of the problems that we look to solve for and kind of broaden our aperture of how we try and help insurers now, it's really around winning the right risks, making better pricing decisions, and then maximizing portfolio profit, So everywhere from ingestion through to quote and then subsequent kind of portfolio optimization. So that's seen our product capabilities, even over the last twelve months alone, evolve from just the pricing and rating capability that many of our customers know us for towards having triage as well as portfolio intelligence capabilities on the on the kind of the back end of that decision making process, as well as releasing a whole host of AI capabilities and AI agents to come sit on top of that decision infrastructure.
00:04:32 · Richard Gunn, Matthew Grant
[00:04:32] S2: Yeah, sure. So, you're right. We are kind of most commonly known for our pricing and rating capabilities. Our mission has always remained consistent over the last eight years. Lots of things have changed, but our mission hasn't, which is to build the decision infrastructure for the insurance ecosystem. And that started with majoring on pricing and rating. In terms of the problems that we look to solve for and kind of broaden our aperture of how we try and help insurers now, it's really around winning the right risks, making better pricing decisions, and then maximizing portfolio profit, So everywhere from ingestion through to quote and then subsequent kind of portfolio optimization. So that's seen our product capabilities, even over the last twelve months alone, evolve from just the pricing and rating capability that many of our customers know us for towards having triage as well as portfolio intelligence capabilities on the on the kind of the back end of that decision making process, as well as releasing a whole host of AI capabilities and AI agents to come sit on top of that decision infrastructure. [00:05:30] S1: How do people buy from you? Is it still the pricing platform? You have to buy the pricing platform and they buy the add ons, or are the add ons something people can get in their own right?
00:05:30 · Matthew Grant, Richard Gunn
[00:05:30] S1: How do people buy from you? Is it still the pricing platform? You have to buy the pricing platform and they buy the add ons, or are the add ons something people can get in their own right? [00:05:38] S2: It will depend on what their current pain points are. We might have clients who initially want to solve some of their ingestion and triage or are more focused just on the pricing. One of our kind of key differentiators is the fact that we can surface up some of that pricing and rating logic at the point of triage. So typically, we do have early conversations around how that can sit at the center of your ecosystem. Ultimately, we'll work with customers and understand what their priorities are focus on that. [00:06:01] S1: There's so many choices now for companies who they can work with. I mean, also choices about do they go with organizations like yourself now semi established, meaning you've out there for seven, eight years testing it out, there's some people now coming in, good understanding of generative AI, agentic AI, but don't really understand insurance, they can build it themselves. My sense is you sort of fit in the middle there somewhere, which is you've got a track record, you can help people grow, but they're not risking it by starting off with some very smart people that haven't really got understanding of insurance. You've got some smart people and you've built a business now, and now you're responding to the needs to sort of grow beyond that original core functionality just up and down the work stream. Is that a fair way of characterizing it?
00:06:44 · Richard Gunn
[00:06:44] S2: Yeah. I would... A key way that we've differed to other solutions in the market right from day dot is we refer to ourselves sometimes as a pro code platform. So you can log on to our platform, and you can operate in an IDE or development environment where you can actually code and build your own triage, pricing, rating, or portfolio intelligence tools. And therefore, we try to position ourselves as kind of the the best of both in terms of build vBuy to that point there, because you have the flexibility that the specialty and large commercial market demands in terms of being able to engineer for your own edge cases as a specific insurer, reinsurer, or MGA, but then you have that kind of enterprise credibility and confidence from sitting on a platform which has been tried and tested. We have, I think, 60 different clients now collectively writing over $50,000,000,000 of premium on our platform, so there's lots of kind of performance edge cases that have been uncovered and had to be fixed in the meantime, we can give customers that confidence around the enterprise grade engineering, but they can still build their own capabilities on top of it.