InsTech - insurance & innovation
00:01:07 · Matthew Grant, Diya Sawhny
[00:01:07] S0: As it should do, customers have to take priority. Since we started lining up this discussion, you've acquired two companies in the meantime just showing how busy you are in both aspects of your job. But Moody's themselves, now talk a little bit about that, familiar to probably a lot of people through the financial services side. But when you are offering solutions to insurers, how should people think about what Moody's is doing today and how you're looking after those customers you just referenced? [00:01:29] S1: When people think about Moody's, obviously, it's a brand really well known in financial services through our ratings franchise. But on the Moody's Analytics side, we also have a pretty remarkable business that's grown both organically and through acquisition. We started out with a lot of products, ratings, so on that were being consumed by insurers but then grew into a life business. We have products that address capital and scenario modeling as well as on the lifestyle actuarial modeling. And then almost six years ago, we acquired RMS. So that really put us on the map as far as property and casualty. But we didn't stop there. We acquired in the casualty space a company called Credit Cat and then to round out our property offerings going deeper on the underwriting side, a company called Cape Analytics. So these are all kind of now part of the Moody's Insurance Solutions business along with a number of other products that we offer to us and insurance customers. Ian, if you want to go deeper on any of that.
00:02:37 · Matthew Grant
[00:02:37] S0: Well, both those companies, Credit Cat and Cape, excellent companies. We had them as as members for a while and got to know them very well. I mentioned in the beginning your role is around organic growth and inorganic growth. But actually, there's really three categories, aren't there? So you're looking at who you're acquiring, how you're growing internally. But this is a middle area, which is partnering. So two questions really in here. Have you seen the the InsTech market move since you acquired RMS six years ago? And and how are you thinking about that kind of middle ground of partnering when it's kinda not right to acquire and you don't want build yourself?
00:03:10 · Diya Sawhny
[00:03:10] S1: We have a very kind of robust DNA at Moody's in terms of leading with inorganic growth, whether it's acquisitions or partnerships. We have a corporate development group that we partner with very closely from a business standpoint. And so the financial discipline of doing anything alongside the industrial logic for any of this is pretty important. Right? And so those are kind of the bookends. Right? Completely organic strategy, completely inorganic, and then partnerships somewhere in the middle. We really are thinking about where are our customers at and meeting our customers and where do we want to directly have a presence and where does it make more sense for us to partner. We have put out a number of partnerships at the Moody's level with the likes of Amazon, Microsoft, Anthropic, just Google yesterday. So that's all about meeting our customers where they are. That's about distribution, where our customers are consuming our products and so on. But then we also have our intelligent risk platform, right, where the cap modeling community and the underwriting community, so they're coming to us. I wanted to double click just a little bit on Credit Cat and keep just building on the success with RMS. Right? With Credit Cat, they were independent and continue to serve the market from a casualty cat standpoint, bringing sort of the analytical rigor that the casualty market is seeking, which from an overall tool standpoint, we think there's a ton more to do there. Right? We think about the size of the casualty market in terms of just written premium even, GWP of over 300,000,000,000, larger than property even. So we really thought that this would be a unique sort of foothold for us to keep building. And then you combine that with where Moody's across the board were investing, right, in terms of whether it's credit analytics, 600,000,000 entities that we cover from an overall financial ownership, adverse media, etcetera, etcetera, seem to make a lot of sense there bringing that together. But then making it very specific for the insurance industry, right? Well, how do we make use of all of this data and the assets that Moody's has but focus it in on where insurers would find it useful. So that was the story with casualty. With CAPE, it was, okay, with our mass cap modeling, really strong reputation in the market.
00:05:43 · Diya Sawhny, Matthew Grant
But then Cape helps us extend our capabilities even deeper on the property underwriting side. The aerial imagery that is then turned into risk insights. Right? That's where we really thought that was bringing a unique capability to us. And then combining it together has that force multiplier effect. And on the other side, enhancing our cap modeling with some of the attributes that CAPE brings, things like roof condition or tree overhang, yard debris, secondary modifiers that can make our models even better. But we're not stopping there. Right? We want to continue sort of growing and investing and really take our cues from our customers is how we look at it. [00:06:27] S0: And those secondary modifiers you mentioned can actually be responsible for quite a significant amount of damage such as masonry chimneys toppling over in earthquakes and landing on roofs. I'm just seeing that myself when I was out in in the Northridge earthquake, but it'd be a very important part and definitely something I could see why Cape, you know, can add some value on that. But I wanna come back to you. You mentioned 600,000,000 companies that you've got data on, and you could allude to this, but it'd really helpful to understand a little bit more about what that means in practice because there's a lot of interest amongst insurers, as we know, in augmentation of data and finding third party data solutions as well as unlocking data they've got themselves. How do you sort of extract value from the data that you've already gathered and bring that across into the insurance side of the business?
00:07:06 · Diya Sawhny
[00:07:06] S1: The data estate, as we call it, sits across Moody's Analytics. Right? So includes information on, I mentioned earlier, 600,000,000,000 entities, all the ownership linkages. So you want to investigate something that looks like a small or medium business, but maybe it's part of a larger ownership chain. You got 2,000,000,000 ownership links sitting over there, tens of millions of risk profiles, 35,000 rated entities, a billion individuals that we follow and track, And lots of deep financial and research content, things like adverse news and so on. So when you think about the use case for insurance, we thought really kind of connects very well with the world of casualty. Whether that's financial lines, things like d and o underwriting, surety, trade credit, and so forth. But then also things like onboarding and compliance checks, various ownership analysis that could be pretty useful at the front end of any sort of onboarding process. So casualty is one big area and then onboarding and compliance. And then the third area we're starting to look at is could there be any application to claims and fraud. When you think about all of these, right, Moody's Data Estates, some of the investments that we're making at Moody's generally could have a pretty significant impact to how insurers are doing business and making it very specific for their context, for our customers in insurance solutions. Since it's not a generic solution, it's very fit for that particular use case.
00:08:46 · Matthew Grant
[00:08:46] S0: This area of financial lines is relatively new in terms of the application of modeling, certainly relative to what's been around for about thirty or forty years in in property. Are there any examples you've got just to help understand what that might mean in in practice?