Making Risk Flow | The Future of Insurance
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.
00:23:22 · Simon Cooper-Williams, Juan de Castro
[00:23:22] S1: In terms of like engagement with that system as well from that front end underwriting, there must have been such a big amount of improvement. I mean, like a similar example with us on like how we would develop. You'd spend a lot of time developing a spreadsheet with an underwriter, and they have to give a lot of their time for that. So it's on top of their day job is iterating with you, developing it. And like, we've observed people have been filling out these spreadsheet raters for years. They put a lot of value in, but then the effort they put in is equal to the value that they get out, and that's where you lose them. So they do this and then dashboards. They don't get data. They don't get analysis that uses the data they put in because it's not accessible. And that's just one of the biggest sort of limitations around that legacy spreadsheet system of a pricing system, which a lot doesn't work. [00:24:13] S0: I mean, there so many issues with that, right? I mean, I've seen the first thing is how do you make in the previous role, right? How do you make sure everybody's using the latest version of the spreadsheet? Even something as that, right? Because if you're distributing the spreadsheets via email, that's probably not...
00:24:13 · Juan de Castro, Jamie Wilson
[00:24:13] S0: I mean, there so many issues with that, right? I mean, I've seen the first thing is how do you make in the previous role, right? How do you make sure everybody's using the latest version of the spreadsheet? Even something as that, right? Because if you're distributing the spreadsheets via email, that's probably not... [00:24:31] S2: Yeah. No, like, how do you make sure that you've got everyone on your email distribution list? How do you kind of, if someone corrects the spreadsheet, like you say, how do you make sure everyone's got the most recent version of the truth? And it just becomes this nightmare of trying to manage a tangle of other things, as opposed to having like a true production system or solution in place where everyone knows where they're working from. [00:24:54] S0: Exactly. And then the other challenge we've seen is then, as you said, Simon, you've got all these underwriters filling all these spreadsheets, the inputs to those spreadsheets get lost. That's not data that's stored anywhere. It's stored in a file system, but it's not discoverable, right?