037: AI in MGA Underwriting and Claims: How Data, Automation, and Efficiency Win with Gavin Lillywhite of Xceedence

clearly, you know, service provider, you know, resolving solutions for clients across the whole holistic thing, as you say.

So I know we touched upon before, before we started this conversation, you know, a lot of exceedance staff are sort of trained insurance professionals.

So through that lens, you know, share with us around how you see current market dynamics, you know, sort of opportunities, you know, headwinds, and how exceedants are sort of navigating their clients through, you know, those challenging times, you know, where do you shine in those areas?

Yeah, so obviously we've been through recently a hard market, which was roughly sort of three, four years.

We're now in this softening market, which of course brings with it new challenges.

And obviously with... softening market by default, you're losing rate strength, right? And we tend to start to see claims going up as well in that period as well.

So that's when clients can start to look at, okay, if I've got to think about giving away rate strength and potential profitability, how do I balance that? Well, I can balance that by managing my costs.

And obviously one of their biggest costs is operational costs.

And I think for us, this is one of the big untapped opportunities for both exceedance, but also more widely for the market.

Because I don't think investors are prepared to just take another round of softening cycle and just accepting costs on the on the way that business used to be transacted and quite frankly there's no need to so I think what we're trying to say to clients is look actually it's time to really automate and agentify your operations so that you can really future proof for this softening market I mean who knows how long that softening market will be If we think about really the really, really last hard market prior to the last one was really after September 11.

And then we had almost 20 years of attritional reduction in rate.

So by default, I think now that there'll be less appetite for a longer cycle, but I think it's now time to sort of really fix the roof while the sun is shining.

So we're helping clients augment their data.

Yeah.

and so that they can then understand their portfolio quicker, better, more reliably.

plus they can face off to investors, and maybe we'll touch on that later around some of the investment into the MGA space, but they could also structure their data so that they can correspond and respond to all of their insurer stakeholders, because particularly for those MGAs that are writing multi-line from multiple capacity providers, Allianz might want their data in one way whilst Zurich or AIG want it in a different way, but you don't want to have to keep doing it three or four times So you want to augment your data properly in the first place so that you can just pick and choose what data you actually send down the line.

And, you know, you probably sort of see this question coming way over the hill quite quickly.

So, you know, margins get squeezed in a softening market, as you've alluded to.

So what would be sort of your key message to all of your sort of clients? Obviously, you've given that message and potential clients that Even in an environment where margins are being squeezed, when they say, well, margin squeeze costs, liquidity is a bit tight, how can exceedance help that in terms of resolving those solutions? Because clearly what you are articulating there, you're not immune to understanding when margins are squeezed, where actually some organisations don't get that and they then come in and spend a load of money and go, well, hold on, margins.

You know, how does exceedance address that sort of, you know, we feel your pain, we understand that, but we can still help

you? So when we think about our agentic model, we've essentially built this agentic suite for ourselves, servicing those 350 plus clients, right? So by default, we've been able to validate, test and test the efficacy of that agentic model internally first on our own workflows, because we have to correspond to the same pressures because we're under cost pressure from clients as well.

As a service provider.

So by default, we're able to bring that learning and bring that capability into new prospect clients as well.

So what we're saying is actually it doesn't have to cost the earth, right? Okay.

But you've also got to think about your own as an MGA, your own sort of existential existence, right? Because if you don't do this...