Making Risk Flow | The Future of Insurance
00:14:59 · Simon Cooper-Williams, Juan de Castro
So I'd like to stitch this pricing data on, oh, there's a claims management system there. It might have causation code, but we can't get it. Or the CAT team might have CAT data and we might not have used that for analysis. So insurance, there's a load of data all over place and it's not all in the policy admin system. It can be anywhere. And like what we've got is we've got a structure where really if a portfolio manager says, Can I get that data? We can usually turn it around and get it. If it's digital and it's in the company, we've found a way to work where we can source data and we can push it out. And again, that's just completely changed how we work. We can stitch data on and provide those extra insights that people weren't getting before. [00:15:42] S0: Yeah, and that resonates well. And I think that's also also something I've seen in in in many carriers, which is the way I refer to it is how do you operationalize your actuarial insights? Right? So it's one thing is to produce the output or produce the numbers that you want to do from an actuarial perspective. But then the concept is then how do you enable others to be able to use those insights into decision making? And to do that, you cannot just provide them a spreadsheet or a number, but you need to provide them, as you said, a dashboard, the insight, something that can be used on a daily basis.
00:16:18 · Simon Cooper-Williams, Juan de Castro
[00:16:18] S1: And another point, like back to that sort of underwriter of the future example that I mentioned earlier and relevant to the dashboard. Recently, we've increasingly seen guys, we're employing more underwriters and some of the senior underwriters, just to show how that underwriting culture has changed. When underwriters are joining, they're asking what our solutions are in this space. So they're coming across, we've done a really sort of senior hire recently, and it's what's your dashboarding like? What data do you have? How do you do pricing? Is it quick? Do we have autonomy in our pricing? Can we direct it? And is now for us, of the pulling factors for underwriters coming into the business as well. And it just sort of proves that culture point around that underwriter of the future. When we're seeing these high performing underwriters moving around and coming in, the fact that they're asking, can we see this as part of them assessing a company is very different than what we think we would have seen in the not too distant past. [00:17:13] S0: Definitely. And Jamie, obviously, especially in your current role, you work with many different carriers, insurers. Is this the type of evolution of creation of more cross functional teams something that you see quite common in the industry now?
00:17:29 · Jamie Wilson
[00:17:29] S2: I think so. We definitely see a lot of our customers looking to kind of embed software developer skill sets in their kind of pricing actuarial teams when they're like building out models in HX Renew. I think we also, I've definitely seen kind of almost the other side of things as well, like seeing like a really, a lot of success when pricing actuaries decide they want to specialize in other skill sets, if that makes sense. So like a pricing actuary deciding they wanna become a software developer or a pricing actuary deciding they wanna become a data engineer. And actually, you know, kind of not just saying I'm gonna dabble in it and put all my data into Excel and now I'm data engineer, but like, you know, really commit to learning the skills in that space. And I think kind of there's a lot of where you get actuaries branching out from like more classic actuarial analysis or classic actuarial roles. Think I it can be really powerful because that actuary often, well, if they're, you know, a good pricing actuary should have a really good understanding of the underwriting kind of world and kind of what are the needs of the underwriter or kind of like have a really good understanding of the business context of insurance. And if they can then combine that with a technical skill set. So like maybe it's data engineering or kind of data science or kind of like software development. Suddenly you've got someone who understands what the problem is, has the business context to kind of formulate an answer, and then the technical skill set to implement that answer. And like classically, that's like kind of three different roles, right? It's maybe the underwriter, the business analyst and the software developer. And you kind of play this game of Chinese whispers as kind of the request gets passed down this chain. And then like six months later you get a solution that isn't quite right. But if you can like collapse all of those skills into kind of all of that knowledge into kind of one person or like into a very close tight knit team, I think you can suddenly start kind of seeing like this really great virtuous cycle of solutions getting out much, much faster. Underwriters kind of suddenly getting things in a matter of like days or weeks, rather than kind of saying, I've gotta wait months for this like big project to come.
00:19:30 · Jamie Wilson, Juan de Castro, Simon Cooper-Williams
Or I'm gonna go and submit my request for data. It's gonna go into this like wide pool and then something, kind of maybe months later, a BI analyst will look at the original request and try and figure out what I actually wanted. So I think kind of, I definitely, I've seen a lot of actuarial teams and like kind of my previous team did this as well of like bringing in non actuarial resource into an actuarial team and seeing success. But also seeing the flip side of actuaries kind of moving away from classic actuarial roles and seeing a success because if they bring that, then suddenly you've got this combination of skills, which is great. [00:20:05] S0: That makes sense. Almost at the core of what both of you are saying that it's this concept of moving from the actuarial team, producing a spreadsheet that underwriters use into a kind of into the pricing actuaries becoming much more a source of insight and enabling underwriters. So let's almost like go through the before and after, and to bring it to life. So perhaps starting with you Jamie, Let's start with the... What did it used to look like? [00:20:39] S2: What did it use? I've got a really nice example. Because in my previous company, [00:20:45] S1: the kind
00:20:45 · Jamie Wilson
[00:20:45] S2: of the pricing actuarial team, like we had to kind of push out rate change analysis and reporting from all of the data that was captured in the pricing tools at the time. And the way that that worked was each actuary wrote some very hacky code to pull out data for their pricing tool. And they ran that maybe once every few months. They realized the code was wrong. They would try and correct it. They would download that into an Excel spreadsheet and then they'd send that Excel spreadsheet around to kind of all the underwriters in the company via email. And so kind of what it meant was that we had this like horrifically manual process that took, I don't know, probably three weeks of actuarial, the entire pricing actuarial team once a quarter to produce rate change reporting. And then after about five years of doing this, we suddenly were like actually kind of this is kind of at the beginning of the development of the global predictive analytics team I built out. We kind of suddenly realized we can actually take some of the kind of standard things that you would expect from a data engineering structure or like a proper BI kind of work stream. And we kind of effectively brought in data engineering skills, took that incredibly manual process and said, well, let's just build a pricing data asset. Like automate all of the piping of this data. Kind of was running every single day, kind of automate the development of like a web based application report. And so suddenly we kind of moved from this place where actuaries were doing hacky data work and pushing out reports in Excel to suddenly every single person in the entire company had live access to all of the pricing data they could possibly want. So they could go and do self serve data collection. But then we also had like these dashboards, like rate change dashboards that were suddenly live on a daily basis as well. So kind of you had underwriters looking on one screen, they would have their pricing tool. On the other screen, they would have this dashboard, which would show what rate change have you achieved in the year to date, or what price adequacy are you running out? Or like, what's your portfolio look like? And it wasn't... You kind of moved away from this, a whole team of actuaries doing this manual...
00:22:44 · Jamie Wilson
Massive manual effort to push out a bunch of Excel reports to suddenly kind of this thing being live all the time. And I think that's what we're starting to see more and more of, is kind of actuaries and kind of... And to be honest, where actuaries don't do this, kind of non actuaries, basically realizing something has to change and doing it instead. But I think kind of effectively actuaries realizing there is a much better way, like kind of more advanced technology exists. There's more advanced reporting. There's more advanced kind of data kind of tooling and coding at the heart of a lot of that as well. Like kind of actually getting upskilled in coding in order to kind of like push out these more advanced solutions.