Making Risk Flow | The Future of Insurance
00:04:50 · Jamie Wilson
[00:04:50] S2: Yeah, sure thing. So yeah, I'm a, I guess a pricing actuary through and through a bit like Simon was describing. So I kind of started my career in consultancy after a few years of kind of perfecting my PowerPoint art. I moved in house and was a pricing actuary in the London market, kind of moved across various lines of business, kind of always working quite closely with underwriters. Spent a few years in Chicago in The US heading up a pricing team over there where I started to move a little bit more towards kind of like data driven predictive analytics, machine learning, data science type kind of like work. And then after a few years of being in Chicago, I actually then came back to The UK to head up a effectively establish a kind of a global predictive analytics team within the pricing function. So kind of it was building out a team of data engineers, data scientists, and pricing actuaries who kind of effectively became data scientists to try and really start pushing for like more data driven pricing within the company I was at at the time. And kind of we got involved in all sorts of things. So we kind of, we were there predominantly for predictive analytics, but we got involved in all of the discussions around data and technology. And we were trying to push things out and like come up with like really innovative solutions. And it was a lot of fun, but it was just, it was quite an interesting blend. It was a very, very different role to I think a classic pricing actuarial or a classic actuarial role. And then at the beginning of this year, I actually then moved from being in house in an insurance company to joining Hyperexponential. So kind of a technology company. And here I effectively partner with our customers and try and help them to get the most out of the platforms. So getting them to think about, okay, well, if I'm moving pricing models onto a kind of a really innovative technology platform, how do I get the most out of that? So like trying to get actuaries to think more around technology and transformation. And then there's also an innovation arm that comes with that as well of like, how can our customers innovate on the platform as well? So that's a little bit about my background. Very similar to Simon, very much starting in pricing and then slowly starting to meander away from classical roles, I'd say.
00:07:06 · Juan de Castro
[00:07:06] S0: And that is one of the reasons why I wanted to bring both of you into this episode. I think listening to your introductions, you talk a lot about insights, about predictive analytics, right? Which is, are things that probably often are not top of mind when people think about an actuary. Well, probably wrongly so, but reality. So again, we'll deep dive into that into a second. But perhaps following up with you, Jamie, let's start with what is an actuary? Like what is the role of an actuary in an insurance company? And I'm sure many people are familiar with it, but other listeners might not be that familiar.
00:07:44 · Jamie Wilson
[00:07:44] S2: Yeah. I'm never too offended when someone doesn't know what an actuary is. I feel like it's quite a niche job. But yeah, I guess one of the ways I'd describe it, so kind of maybe a little bit of history of actuaries really. So kind of like the actuarial profession really started in kind of life insurance and pensions. So kind of it was effectively this statistical study of when are you most likely to die? And like, how can I then like use that analysis to figure out what money do I have to hold in order to pay out for life insurance and things like that? So it kind of very much started in that space. And it was very much embedded on this idea of statistical analysis, but kind of starting in mortality. And then I think kind of over time, there was this realisation that actually, well, within general insurance, there's a similar need for kind of like statistical analysis to try and figure out, okay, I'm gonna have to pay out claims over a number of years. So therefore I need to know how much money I need to hold back for that. And so kind of you started to get the movement of actuaries into kind of the insurance world, but very much in that kind of reserving space. So very much in like a regulatory, how much money do I need to hold in order to pay out claims? And so kind of much more like that third line of second, third line of defense of, okay, well, once I've written the business, how much money do I need to hold? And then I think kind of what's happened over the last twenty years is that kind of the actuarial profession has kind of become more and more embedded in the kind of the insurance industry and moved away from just reserving. And now you kind of hear about capital modelling actuaries, reserving actuaries, then and crucially kind of the latest breed, let's call it, of pricing actuaries who are actually there, who are meant to be kind of like helping underwriters to figure out how they should be pricing business. And that obviously looks very different. A pricing actuary looks very different in retail insurance to kind of SME insurance to kind of large commercial specialty insurance. But kind of always, I think kind of coming from that background of like trying what you would hope that they're kind trying to apply statistical analysis to figure out some kind of outcome for the business.
00:09:47 · Juan de Castro
[00:09:47] S0: Okay, so it sounds like even within the actuarial teams, there's been quite a lot of evolution in the last few years. And again, we don't often talk about transformation of the kind of the actuarial teams. So Simon, like when you think about this evolution that Jamie has referred to, like how do you see the evolution of the actuaries in insurance companies?
00:10:09 · Simon Cooper-Williams
[00:10:09] S1: Yeah, I mean, think looking at what's happening in Markel, the demand from the business for data and analytics has just increased so much. So we talk about actuaries evolving in the insurance industry, but I see the underwriting part of the insurance industry has evolved for them to be a lot more demanding for that analytics. So, I mean, we have a program in Markel called Underwriter of the Future. That wasn't something there when we started. And a lot of that is around sort of technical capability of underwriting. So it outlines segmentation, it outlines expectations of portfolio management capability that various levels of underwriting divisions should be doing. So we've now got underwriters who are looking at these frameworks and saying, okay, well, I should be able to segment my book. I should be able to use pricing data to stitch on top of it. The people who are really well placed to do that are the actuaries who've been sort of been trying to do that for years, maybe on a different floor historically or somewhere else not sitting with them, but I think they've evolved with the underwriting business at the same time. So you've now got that demand and actuarial skill sets are very well placed to help with that. Like the bread and butter is slicing and dicing data, stitching things together, dealing with really messy sort of sets of data where they're not easy to analyze. It's not standardized. It's picking it apart. It's making sense of it. It's trying to put judgment on top of it as well. And I think that's really brought them to evolve with the underwriting function at the same time. And that's where I think where traditionally, actually, it may have been in more the sort of second line functions. You can see them in that first line now because they're there to help make the decisions on front line. I think that's where they can add a lot more value compared to historically.
00:11:54 · Juan de Castro
[00:11:54] S0: Yeah, and that's probably, I think, of the evolution also Jamie was referring to, right? So from being a reserving actuary where you probably need to work less day to day with underwriters to being more pricing actuaries, where, as you said, at the end it's about enabling underwriters to make the best decisions about the risks. You are mentioning there the kind of the evolution from what actuaries used to be more in the past, which was reserving actuaries, and you mentioned them being in a different floor, etcetera, to working closer together with underwriters. And I guess that also has meant that the actuaries themselves have have had to evolve and also like probably become more cross functional in the way they those pricing actuaries work. So I'm sure based on your kind of experience in the market, what type of actuarial teams do you see are most effective? And perhaps also on the other side, some examples of when they are not that effective.