InsTech - insurance & innovation
00:16:06 · Richard Gunn, Matthew Grant
[00:16:06] S2: Yeah. I've heard that before, and I can relate to that. When we were first expanding into The US, one of our investors, he's a director, he shared a kind of some of data that they'd analyzed, think, just the kind of VC portfolio level, and it was looking at expansion from The US into The UK and from The US into Japan. And the likelihood of success is actually higher going from The US into Japan. And it was like... The theory is that because when you're expanding to the Japan, you know it's gonna be very different. You know that you're gonna... Like, do you need a JV or a partner? You know that they speak a different language. It's very clear they speak a very different language. Their markets work differently, so you approach it through that lens. Whereas people take for granted when they expand from The US into The UK that they speak the same language, it's broadly the same market, and therefore we'll be successful just by pattern matching what we've learned in The US. That's something I've tried to internalize over the last year, tried to, like, force myself to reiterate our operating model, reiterate how we kind of approach the market, think about things from zero to one, kind of first principles, to make sure we don't fall into that trap. [00:17:08] S1: And, I mean, you've got the not not just work experience, but you've taken your family over there. How's that going for all of you having to adjust with young children to to living into a different part of the world?
00:17:08 · Matthew Grant, Richard Gunn
[00:17:08] S1: And, I mean, you've got the not not just work experience, but you've taken your family over there. How's that going for all of you having to adjust with young children to to living into a different part of the world? [00:17:17] S2: It's been fun, for sure. A four year old and a three year old and and another on the way, and we live in... Down in Brooklyn. So some people in New York would say, therefore, I'm not living in the real New York, and some people would say, I am living in the real New York. Although I'm down in Park Slope, so I don't think that can be kind of considered edgy Brooklyn by any means. One benefit I found from New York, and maybe this is just being an expat, and my... Most of my experience as an expat is in New York, and therefore I'm just applying it to that. But it feels like there's quite a lot of transient communities in New York, which makes it much easier to actually make friends and build a network. And so I found it... Like, unsurprisingly, found myself hanging out with a lot of other people who have intersection with insurance and technology, having moved to New York, but that's part of fun of it.
00:17:57 · Matthew Grant
[00:17:57] S1: Let's come back to the AI. We're watching this real because everyone's talking about the topic, can we drill down to what difference it makes? There's one application you had that I was really fascinated by, is not so much core business, but helps you run the business, which is your use of Gong, which is a tool that you use to, as I understand it, to listen into the conversations or they initiate it, but your sales team is having, and then the tool actually scores people on the quality of the conversations they're having and actually records the information obviously with the client's permission or prospective client. But I'd love to learn a bit more about that because it sounds very intriguing and it's a very practical application of the use of some of the new tools coming out.
00:18:38 · Richard Gunn
[00:18:38] S2: Yeah. So, unsurprisingly, we have put a big emphasis on how we can leverage AI internally. I would refer to Amrit as a... Who's our CEO and and cofounder, as an AI maximalist. And we internalized very early on kind of the mantra that you need to work out how to leverage AI better and faster than your customers and your competitors. And if you do, you will win, and if you don't, you will lose. And kind of that is what motivates me to make sure that we're not just thinking about how do we build agentic capabilities for our clients to use, but also how do we use them internally. Because if we can be 10 times more effective as a business, then we could deliver much more value for our clients. So specific to Gong and the go to market function or the revenue function, that's quickly become kind of table stakes to have some form of recording capability and then leverage AI to evaluate how those calls are going and how you can improve. Some of the areas that we look to do that, like, one is to support forecasting, for example, because you can scan those scripts and identify where you should have more confidence. And maybe we'll add some waiting now based on the words that they use in New York versus in in London, thanks to your guidance there. One area that we've recently built out, which is really, really cool, actually, we have business value consulting capability, so that's about working with our clients to, first of all, understand the value that they should get from our platform. And then once we bring them on as a customer, it will be... We'll go through business value planning, so, like, what's the most effective way to bring value to the business as fast as possible, and then we'll do a BVR, business value realization. So a year on, did you get the value that you expected from our platform? And if not, how do we need to approach it differently? And we've now found a way that we can do... We can pull our early conversation transcripts from actuaries, from underwriters, actually into court code, and then use that to create the first version of a business value report. And so rather than saying, wait, I now need to book in time with your underwriters and your actuaries, we can actually say, look, we've listened to our first five hours of speaking with you as a prospect.
00:20:23 · Richard Gunn
We know we're moving towards a kind of a proof of concept or a proof of value. But just to give you a high level based on the pain points you've surfaced and our viewer benchmarks across our 6E customers, this is the level of impact that a project like Hyperexponential might be able to have. Does that align with your expectations? Does that surprise you? What are we missing? Because obviously we'll be missing stuff at that point. We're not going to solve for it all without a specific kind of project related to it. That's just a great example where previously... Like, we built a team of many ex McKinsey and other kind of big four strategy consultants who would have spent hours and hours around that, and now we can run that out very quickly, and they can spend their time actually challenging it, seeing where the gaps are, and making sure it's specific to an insurer and reinsurer rather than a more generic cripple because you're spending a lot of your hours just doing heavy lifting.
00:21:08 · Matthew Grant
[00:21:08] S1: I'm glad you mentioned that point about pain points because... I mean, no surprise, it sort of goes back to Amrit's background when he was an actuary, he'd also, can feature engineer, software engineer, so he could write code, he said, I understand from him, there's some things he wanted to do, couldn't do it when he was working for an insurance company and built a company to solve it. Actually, interestingly, we've got a webinar coming up with one of the large US insurers and they're asking them how they deploy AI, and they look for where people are complaining. When they get a complaint from somebody about they can't do something, they go, Right, okay, can we deploy an AI solution here to solve that problem? What I think is fascinating is at one level is we're sort of hearing about companies still struggling to articulate the large investments in AI, but actually in the companies themselves, I mean, I think you're a great example of this, people finding solutions to actually just create that efficiency at the operational level. But then I'm sure you're also finding ways to accelerate both the development of what you're offering to your clients with the hx tools themselves? Is there anything there you just want to draw attention to that is tapping into large language models or agentic AI or other ways of just improving that experience?