InsTech - insurance & innovation
00:04:46 · Jamie Wilson
[00:04:46] S1: As you referred to earlier, HX started with Amrit looking to solve a particular problem. Amrit and MJ, the two cofounders, and they were looking to solve problems around the pricing part of the underwriter journey. And part of the reason for that was, you know, that's a very high leverage decision point in any underwriter workflow. But in particular, in the commercial specialty world, at least at that point in time, like in the history of HX, it was a part of the workflow where there was a lot of pain points associated with it. I knew that from my own time working in industry. I knew that from kind of industry peers, people that I'd worked with. And so HX effectively looked to try and solve for that pricing problem of can we help our customers deploy pricing models, deploy pricing tools to underwriters at speed, and can they iterate on these pricing tools, drive greater insight to underwriters, again, trying to, like, do that quickly and at speed. And so we saw really great success in that space. But one of the interesting things that started to happen, I'd say more like three, four years ago, we started to see customers pulling us left and right of that pricing part of the underwriter workflow. So, like, pricing is really at the heart of kind of the center of kind of the underwriter workflow. We started to see customers basically saying, can we... That calculation engine, HX, that we currently use for pricing, can we use that for other parts of the workflow? They said, we deploy a risk appetite model here or kind of a predictive model there that's not really pricing? And then we'd have other customers start saying, can we use the workflow components or the flexibility of the platform to start pulling you into kind of other areas like peer review, referrals, authorities? And so we had customers doing that, and they were pushing the platform beyond what it was originally intended to be. So about three years ago, we then started responding to that and build out new product capabilities, features to effectively allow our customers to actually build out a full end to end workbench within the HX platform. So that's where we've got to today. I would have described the platform a few months ago would have been as, like, effectively an AI assisted workbench. I can take a submission in.
00:06:44 · Jamie Wilson, Matthew Grant
I can use AI in various points to help the underwriter as their journey, and I can go all way from the submission going in to a quote going out all within the HX platform. [00:06:53] S0: There's a very interesting Harvard Business Review article, to your point about looking left, looking right, sometimes referred to as upstream, downstream, that's where to look to grow the business. Actually, there's also another quote that I'm sure you're familiar with, which is when you get in the top two or three of the the market you're in, you basically go and expand your market, and and then you obviously go into a bigger market, which sounds like you've done both [00:07:13] S1: of those things. That point around looking left, right, or looking upstream, downstream, that drives a lot of our product strategy. It's like, okay. If a customer is pulling us in that direction already, that's the best place to move. It may be that you as a a tech company are like, oh, this would be great if we could go and do x and y and zed. Ideally, if you've got customers trying to do it in your platform already, but the platform's not built for it, that is the ideal, like, indicator of this is a great space to start moving into. And that's exactly what we did about three years ago as we started to branch out across the end to end underwriting workflow.
00:07:13 · Jamie Wilson, Matthew Grant
[00:07:13] S1: of those things. That point around looking left, right, or looking upstream, downstream, that drives a lot of our product strategy. It's like, okay. If a customer is pulling us in that direction already, that's the best place to move. It may be that you as a a tech company are like, oh, this would be great if we could go and do x and y and zed. Ideally, if you've got customers trying to do it in your platform already, but the platform's not built for it, that is the ideal, like, indicator of this is a great space to start moving into. And that's exactly what we did about three years ago as we started to branch out across the end to end underwriting workflow. [00:07:44] S0: Yeah. Or, of course, you got attention of not doing what you don't want to do. So I guess sometimes you just gotta say no or or maybe not yet to the client that's trying to drive you too fast. And then this Underwriting Survey, you have 350 people respond to it. I've run surveys before. I know how impressive that is. So before we talk about the survey, how did you actually even manage to get that many people to contribute to giving you feedback?
00:07:44 · Matthew Grant, Jamie Wilson
[00:07:44] S0: Yeah. Or, of course, you got attention of not doing what you don't want to do. So I guess sometimes you just gotta say no or or maybe not yet to the client that's trying to drive you too fast. And then this Underwriting Survey, you have 350 people respond to it. I've run surveys before. I know how impressive that is. So before we talk about the survey, how did you actually even manage to get that many people to contribute to giving you feedback? [00:08:05] S1: Yeah. So we partnered with a company called Coleman Parks. We've worked with them before on these types of surveys, and they've been absolutely fantastic at kind of driving that engagement with the surveys. And so what we managed to get to exactly as you're saying, 350 underwriters responding across The US and The UK, all senior underwriters, so lead underwriters or, like, heads of or CEOs, all working in commercial and specialty. So trying to tailor it to the audience that's most relevant to effectively the underwriters and companies that we work with day in, day out of the company. [00:08:38] S0: Before we go on with that, you're gonna make this report available to the listeners of the InsTech podcast, I think, as as well as other people. And that's available on the website, I believe, and they can contact you directly to learn more about
00:08:38 · Matthew Grant, Jamie Wilson
[00:08:38] S0: Before we go on with that, you're gonna make this report available to the listeners of the InsTech podcast, I think, as as well as other people. And that's available on the website, I believe, and they can contact you directly to learn more about [00:08:48] S1: it. Exactly that. So if anyone wants access to that, we're gonna be releasing it in September of this year. So it'll be available through the website. You'll probably see some bits and pieces on LinkedIn about it. If you can't, for whatever reason, find it as you're saying, please feel free to contact me on LinkedIn. I will happily point you in the right direction so you can get access. [00:09:05] S0: You gave me a preview of the report, and it is fascinating. And, no surprise, heavily orientated around AI. One of the themes that came out of this, which perhaps you could just explain it a little bit, I can sort of understand it, but was AI is pointed at the floor, not at the ceiling. I'm guessing that's all about fundamentals, but could you just explain a little bit more about what feedback you're getting related to AI?
00:09:24 · Jamie Wilson
[00:09:24] S1: Yeah. Definitely. And it's this idea around where our company is actually investing with AI at the moment and kind of where do underwriters want support. And so what I mean by that is one of the questions we asked was asking all of these three fifty underwriters, where has AI delivered the most meaningful value your underwriting to date? And unsurprisingly, 51% of them said it was on saving time and on manual admin. So it's very much like lots of efficiency gains. That's where the AI has been adding value. Amusingly, 3% of them said they have received no value from AI yet. So there's probably 3% of CIOs who are very upset about that statement. But 21% said that AI had driven improvements in the quality of the decisions. So you've got effectively, you know, 50% saying AI today, it's all been about efficiency. That's where the values come from. 20% saying, actually, AI is helping us make better decisions. But we asked underwriters a different question to that one, which was what makes an underwriter excellent? So we got them to kind of imagine the best underwriter you've ever worked with. What about them make them exceptional? And the top things that came up time and time again were all expertise and judgment led. So top of that list was risk selection and appetite discipline, and then technical depth and complex risks or commercial instinct on price. All of these things were around technical underwriting, expertise, judgment. That's what makes a truly exceptional underwriter. Speed, efficiency barely registers on that list at all. And so it's this really interesting thing of the industry has effectively focused a lot of AI efforts on, okay, how do we do things that make us more efficient, which is effectively raising the floor. Like, everyone gets a little bit faster. But what underwriters really care about is exceptional underwriting. How can I make better decisions than anyone else? Like, how can I be the best underwriter? And that's in reality that decision, like, Like, how is AI driving value there? And underwriters, the kind of the response we're getting back is actually that's not where most of the value from AI today is coming from. So it's this idea of, okay, the floor is being raised.