How Insurers are Embracing Technology and Change in an Evolving Risk Environment

In this episode of William Blair Thinking Presents, technology analyst Dylan Becker joins Adam Klauber, group head of the financial services and technology research sector, to discuss highlights from the seventh annual William Blair Insurance, Banking, and Wealth Technology Conference. They delve into key trends in the insurance technology space, including labor constraints, legacy modernization, and the integration of AI infrastructure.

Podcast Transcript

00:20
Chris
Hello, everybody. Today is September 12th, 2024. On today's episode of William Blair Thinking Presents, we welcome back Adam Klauber, CFA, partner and group head of the Financial Services and Technology sector, as well as Dylan Becker, CFA. He's an analyst in our Technology, Media, and Communications research group and a newbie to the show. So welcome. Thanks both for joining.

Last month, Adam and Dylan attended William Blair's 7th Annual Insurance, Banking, and Wealth Technology Conference, which brought together executives from leading underwriters, distributors, and technology vendors for a range of panel discussion topics. I thought it would make sense for both analysts to walk through some of the highlights from the panels and use that as a catalyst to talk through overall trends they are seeing throughout the insurance technology space.

So, with that, Dylan and Adam, let's kick this off with a high-level overview of the event, mainly what it's all about and maybe some of the main takeaways. Then, from there, we can get into more specific topics.

1:22
Adam
Sure. I'll jump in and start. And then Dylan please add in.

So, you know, over the last decade, William Blair, Dylan, and myself, as part of the team, have really been trying to delve into how technology is changing insurance. And, you know, from the outside, insurance is a very large business. You know, when you look at P&C, life, and healthcare, together, that's at least a $2 trillion annual market just in the US.

And the core of the business is processing and moving paper around and analytics, and yet the industry has never really been that great at doing those functions mainly because the underpinning of technology has been weak. So, you know, the conference, I think, tries to attack that and say, okay, there's a lot of different avenues, a lot of different companies and segments really trying to change the equation.

So, what we try and do at this conference every year is try and bring a lot of the leading competitors who are trying to, you know, really bring technology into our arguably what's a, you know, bit of an archaic business. Dylan, if you want to jump in?

2:38
Dylan
Yeah. No. It is a fantastic overview. And to Adam's point, right, it's a very large industry that has historically lagged in digitization in its simplest form. So, it's creating opportunity for all of these technology vendors and new carrier-type models to really shift how people think about and interact with insurance. At its core, it's a data-driven business, and all this information has historically been siloed. If anything, we've seen the evolution of risk factors and a push towards more real-time granularity of data that can enhance decisioning, make that more profitable from a carrier perspective, but also improve the end experience for that insured policyholder itself. And as an empathy driven business, that's really kind of where the end-to-end connection and tying that relationship back to the consumer is really valuable.

3:23
Chris
Got it. All right, so let's walk through some of the highlights that you laid out in your conference takeaway report starting first with labor constraints. You're saying that, you know, these are continuing to pressure operations. How so?

3:35
Dylan
Yeah. Yeah, it's great. I mean, I don't know, a large handful of students coming out of industry that go in with the idea of really pushing forward into the insurance industry, at its core. So, again, these carriers have been around forever in some capacity. And there's this aging out dynamic that's taking hold. I think the statistic is something like close to 50% of the industry is set to retire over the next ten years. And so that's another catalyst that's really kind of pushing forward this technology wave. Right? They have to not only be able to better interact with that end consumer and provide a personalized experience, but they also need to modernize their tech stack, think about cultivating, and utilizing that new wave of talent that's coming to the industry and really have to push towards productivity, because managing COBOL mainframe systems that have been around for three or four decades, the people that know the internal kind of legacy tech out of those systems are not going to be around in the next 10 years.

And so that's kind of pushing forward this catalyst of productivity on the back, if you will, of what's kind of being a constrained labor industry in insurance. And obviously this is pushing forward change in multiple other segments as well.

4:49
Adam
And I would add on, I think adding to the hole, the gap, that's building is the fact that insurance is a much more complex business when you drill down to it. It's 50 different states. You have to deal with the regulatory environment. There's a significant legal component. There are two different accounting systems for insurance. So, you know, finding software coding engineering professionals who actually can, you know, apply that complexity into a systems environment, that's not easy to find. So, you can't just put people off the street and say, okay, you know, go to work here. Having people that have that combine industry expertise with a software background is really, really tough to find.

5:36
Chris
I bet. Another one of the takeaways is around the ways in which the rising complexities are adding urgency to legacy modernization. Can you talk through this a bit, especially how, you know, the insurance industry's reliance on data and how it's struggling to keep up with the advancements?

05:51
Dylan
Ya. And I kind of hinted at that in the prepared remarks. But really, we've seen a combination of factors that are pushing forward this change, right? You have limited visibility. We've seen the pressure on inflation and what that means for claims payouts, which is really kind of driving better risk management's emphasis if you will. At its core, insurance is a data-driven model and you have all of this information.

But going back to legacy tech complexity, it's all siloed into separate systems. So how can we unify and standardize that information to drive better intelligent decisioning? Can we get more granular context on what we're actually underwriting and insuring? And then the frequency and severity of risk factors continues to tick up as well too. So, all of those, factors are really pushing for that level of context and insight from a data granularity perspective.

And to really be able to leverage and utilize that, you have to have a more modern system. So that's kind of the step function if you will, that's pushing forward for a catalyst of further innovation and adoption from the industry.

6:57
Adam
Themes that were highlighted in the conference are that, you know, where's a lot of this change happening today? Where is money being spent? Where are the insurance companies and insurance organizations trying to change? And there's a big race right now and, as I'll say, speed to market that the interface with the customers, whether it's business customers or retail individual customers, it's a very clunky process.

And, you know, again, that has to go through regulatory, it has to go through the company's systems and in part also the go to market or the customer facing side is actually split from the insurance company because it's usually handled by the insurance agent. So, all those, you know, wrapped together it's a very challenging process.

So, insurance companies are spending a lot of money on their go-to market, trying to speed up the process, make it more efficient. And interestingly, the brokers who had not traditionally been leading on technology are spending more money also on their go to market, trying to bring, in particular, a lot of data analytics to the point of sale effectively.

So yeah, there's a ton going on right now.

8:10
Chris
Yeah. Data seems to be a thread through a lot of this. So, let's just stay on that topic of data. One of the panel topics you highlight is how AI infrastructure is being used to capture the vast volume of data across the ecosystem and transform it into usable insights and broad-based automation. Let's dig into that a bit.

8:29
Dylan
Yeah. And I'll start and pass it over to Adam. But there's, again, there's a number of factors here. I mean, generative AI in the software landscape is a topic in the C-suite for every business, for insurance, or anything else. But certainly, given Adam's point on how regulated the industry is and how you have to manage hallucinations, there's a little bit of kind of skepticism on what's hype versus reality, if you will.

Going back to kind of how we address the historical productivity, labor, and efficiencies across the ecosystems, and what that can mean from an underwriting and claims adjustment perspective from a cost-saving basis as well, too. There are a lot of value-based use cases here that can look to be adopted from a carrier perspective, but it's really around how do we tie those heavily regulated workflows and processes with industry-specific and heavily curated data, whether that's structured or unstructured?

So, we have to be able to synthesize that information to drive it from an intelligence perspective. And then what do we do with that data to improve how we operate as a fundamental business? That's kind of the core driver on productivity and I'm sure Adam has a has a good perspective here as well to.

9:38
Adam
Yep. This goes back to the earlier comment on the race to go to market that, you know, the conundrum for insurance companies is they want to use the analytics and the AI capability, but, you know, the systems as is aren't really allowing them to so there's a number of very good, nimble software vendors out there who are really in what I call enabling the process.

And you know, there's different ways to slice an apple, but a lot of it really has to come down with building very rapid data lakes, data sets, and software that control those or, you know, control and continually evolve those data lakes and data sets on the fly because the systems generally can't do that. So, there's a handful of these again, really, really good, you know, I'll call them stopgap companies out there who are beginning to allow that happen.

And, you know, that to me is where the Wild West is because the industry, while it is based on analytics, traditionally their data is relatively static. They use a couple of providers and their own their own data. And it's very cumbersome getting that data into the workflow process again, particularly that front-end process. So, you know, AI use is coming up at the same time as a lot of companies are looking to open up that process. So yeah. Yeah, it is the Wild West right now.

11:10
Chris
All right. And then when it comes to data optimization, you wrote that the use of generalized data points at the community or regional level to assess and underwrite risk is no longer sufficient, given the increasingly complex risks impacting the insurance market. And then, at the same time, you wrote that insurance companies are facing an influx of data, through both internally generated means and the availability of third-party data sources. What is the proposed solution in this case?

11:38
Dylan
Yeah, I think it is somewhat simple and what Adam kind of just hinted at, right? You have to get more granularity on what you're collecting and aggregating that data off of it. It needs to be more real-time in nature, right? In its simplest form, historical actuarial models are based on a 20-, 50-, or 100-year time horizon; those are irrelevant anymore, right? Because we're seeing the frequency and severity of risk tick up as the evolution of a particular kind of category that's being underwritten evolves pretty substantially. So, the number of risk factors is only accelerating, which is placing that emphasis on not only the data granularity piece, but also being able to adjust and adapt to that at all times.

12:15
Adam
And you know, to layer on that, again, this is the part of the business that is accelerating very quickly because the challenge for an insurance company is just bringing outside data by itself, one, it was a challenge because the systems didn't work with outside data that well. And two, that data didn't meld that well with their existing, what really is the loss data, which is going to drive the pricing and underwriting. So, it's taking the insurance companies, they've been working this number of years, and this is going to be a decade work in progress. The ability to bring in those outside cohorts, both from a functional standpoint but also from an analytical standpoint, and work with their actual loss data. And so that really is still in its infancy. But the early results are looking pretty good.

13:07
Chris
All right. And then another theme you highlight talks about the ways in which data integration is creating new opportunities for risk mitigation. Can you elaborate on that one a bit?

13:17
Adam
Yeah, I'll jump in. Yeah, there's a cadre of new companies coming up that typically insurance is all based on, you know, predicting the loss but not on stopping the loss. And there's a handful of new companies in cyber, in commercial auto, and wildfire that are taking a look at the risks and say, okay, this is what your risk looks like if you can do X, Y, and Z, you're actually becoming better risk. So you're going to be at a lower chance of loss and pay a lower price. And while that seems like an obvious, that's a practice that really has not taken hold in insurance, but as what we're seeing as the world is just becoming much riskier. And whether it's a lot of weather volatility or a lot of litigation volatility, the necessity to actually mitigate risk at the front versus just, you know, trying to avoid it. It's still early. I guess on the earlier stages. But you know, over the next five, ten years that's going to become a much bigger part of the insurance industry. And I know there's some really cool companies and vendors out there helping both the companies and also the clients begin to mitigate the risk.

14:30
Dylan
And you're starting to see this, right? As Adam's well aware, too. On the MGA and the MGU side of the market where you get to that specialized underwriting framework, we're seeing some legacy carriers exit markets where they can't efficiently or effectively price risk. And so it kind of has this fortuitous cycle that that Adam is calling out, if you can better manage and predict that that risk, you can also price that more effectively from a policy perspective.

It enables you to win more business and do so more profitably, so it accrues to kind of both sides of the policyholder spectrum here.

15:01
Chris
Now, moving beyond data. Let's touch on the continued opportunity to improve the customer acquisition process. You mentioned that despite some progress over the past decade, there's still significant opportunity for carriers and brokers to improve customer acquisition efficiency and generate a competitive advantage. Let's talk through that one.

15:21
Adam
Sure. I'll jump in and then Dylan. So, there are there are a number of fronts. I mean, there is the contact with the customer. There's the go to market. There is the processing and service side that, you know, insurance is still a very cumbersome business. So, there's a lot of paper involved.

And, you know, it's a well-known secret within the industry that it can take days and days and days just to get the application right and weeks to get a policy bound because the inefficiencies in that system. So, you know, that's part of it. The other part of it is on the commercial side, so business insurance or retail side, it's very expensive to acquire customers. And we do a lot of analysis on LTV. So, there are LTV to Cat, long-term value to Cat, and the industry, some of the leading players have been looking at that metric. And more and more of the industry are trying to look at, you know, how can they get their LTV to Cats to a much more rational level? That takes a lot of analytics and takes a really good system to benchmark a metric that wouldn't have been possible for a lot of these companies five, ten years ago. That's much more come to the forefront today.

16:33
Dylan
Yeah. And the only piece I'd add there, too, is the retention angle, which is a big component of that as well. It's not just winning the policy upfront; it's "How do I retain that customer?" whether I prefer to or not. Right. You should have a good view of that life cycle over time.

But particularly if you can provide that kind of tailored handheld claims experience in that event when that customer is most susceptible, and this goes back to the point of the empathy-driven industry component. That's a substantial retention tool for those customers in tailoring that personalized experience, which will help obviously massively on the on the customer acquisition side.

17:11
Chris
All right, so finally, one of the last takeaways is that insurers and MGAs are facing a more dynamic landscape for risks in products, making them more receptive to new software providers that can allow them to enter new markets in as little as a few weeks, even to a few months. Can you talk through this a bit?

17:31
Adam
Yeah, I'll start on this one. So, the world's becoming a riskier place. There's no doubt to it. And the traditional insurance, which is, you know, their business is handling risk, but it's been done on a very static basis. And when you see new risks, like wildfire or cyber that ten years ago, you know, that really was not on most companies' radars, people's radars, or insurance companies' radars.

So as these new risks come up, there's a change in the nature of insurance. And this is one of the biggest megatrends that we're very focused on is becoming much more of a bespoke or tailored market. Now, that's one of those easier said than done because the systems, the regulatory, the legal systems, that's really tough to do.

And that's where bringing Dylan and you know, that's where Nimble Software is, you know, beginning to make a difference. Dylan?

18:28
Dylan
Yeah. Yeah. No, I mean, if anything, the purchasing mechanism and how carriers interact with the end policyholders becoming truly omnichannel. Right? That's creating its own challenges from a technical perspective of how you manage the flow of information there. But there's also a shift in how you actually go to market and quote and bind some of those policies.

To Adam's point, we've seen the prevalence of things like embedded insurance at the point of sale where you can kind of be offered or bundled at the purchasing point for whatever asset is being acquired. You see things like usage-based insurance, where it's more functionally based on miles driven or whatever the channel is there, but it's kind of really an evolution off of consumer preferences that has kind of forced the industry to really be able to communicate and adapt with that preferred medium that the end policyholder looks to communicate through.

19:19
Chris
All right, guys, well, this has been great. For those interested in reading the highlights, you can request a copy by reaching out to us at Williamblair.com/Contact-us. Thanks again for joining us. And let's do it again soon.

19:32
Dylan & Adam
Thanks, Chris.

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