Good afternoon, everyone. I'm Curtis Nagle, the Senior Business and Information Services Analyst here at BofA. The session is Verisk. Very pleased to have CFO Elizabeth Mann with us. This is gonna be structured as a fireside. Time permitting, we can field any questions from the audience. With that, welcome, Elizabeth. Thank you for joining us and looking forward to the conversation.
Thanks so much. Thanks for having me here and thanks everyone for joining.
Great. Coming off your Investor Day last week, lots of new findings, but at least for me, I think one of the most important or, you know, the biggest themes was the idea of expanding Verisk's open architecture, connecting the broader ecosystem. If we look at the growth opportunities, let's say over the next, you know, three years or so, in terms of the adjacencies or, you know, new product lines where you think you could see the most immediate opportunity or upside for Verisk, you know, how would you describe that?
Yeah. Thanks, Kurt. We're particularly excited about our open ecosystem and the ecosystem opportunities that we have in a number of our products. Philosophically, this comes from you know, the opportunity we have. We are so connected to the insurance industry, and they already rely on us for many solutions. This gives an opportunity that's really win-win for us to find and identify new value-added solutions. Obviously, we do some of this organically, but when we see great products out there that we think have an opportunity to really bring value to the industry, we can integrate them into some of our existing solutions and participate usually via revenue share.
This helps bring new opportunities to our customer set, which they have told us they very much rely on. We gave a number of examples of this at our Investor Day, but we could talk more about how we've been doing this in our property estimating solutions business.
Sure.
We're doing this increasingly in our anti-fraud space.
elsewhere across the business.
Yeah. Maybe it would be worth diving into some of the verticals, you know, with the product property estimation. You walked away from a potential acquisition just given, let's call it government friction. Maybe the playbook there, and then, yeah, fraud, which was a big topic in the Investor Day, and yeah, maybe dig into that a little bit more.
Yeah. Yeah. Let me start with our property estimating solutions business, which, as you've said, we, you know, we're really excited about the organic opportunity for that business, both in the products that we're creating and also in the ecosystem that we're bringing available to our customers. Our customers, the customer set for that business, it's important to remember that our property estimating solutions business is a business. It serves both the insurance carriers, it also serves the contractors that are doing the work for property repair that's covered by an insurance claim, and it also covers the third-party adjusters who help facilitate that workflow. We have different solutions for those different groups. It is a workflow that connects that industry and is built upon a proprietary data set.
which is the pricing for to agree on sort of the estimate for property repair work. The pricing. If you think about how this is used, if a tree falls on your house, you call your carrier to submit a claim. There's an adjuster that reviews that and eventually kind of they may well go on site. They can use our software and tools to assess the damage, figure out what is the estimate that should be written, and what is the cost for each of those line items. The line items can be building materials, like how many roof tiles or how many sheets of drywall. It can be the contents of the house, if that was damaged. Was there a laptop? Was there furniture that was damaged?
It's the labor involved as well. Of that pricing data set, you know, some of it may be more transparent in the markets than others, but it's the labor cost that we track in great detail across 460 jurisdictions that is not at all transparent in the market and difficult to replicate. It's the core of and the quality of the pricing data set that's at the heart of the value proposition that's agreed upon between the carriers and the contractors. There it's a two-sided market. They obviously have different, they each want, you know, the prices to go in the opposite direction. It's kept honest by that continued.
agreement. This is fundamentally a network business. To that, actually, we talked on our fourth quarter earnings call about the AI-driven enhancements.
to that process, and the products they're moving from XactXpert, which relied on rules-based and machine learning tools to help carriers ensure that the estimates that they're receiving and approving are in line with their own internal guidelines, in line with regulatory requirements, in line with building codes.
We can move, and we can build on GenAI for automatic photo tagging, as we have done in XactAI. Eventually, we've got Xact Gen now that has generative-based ability to create an estimate.
Be reviewed by that party.
Traceable and, yeah.
Yes. Yeah. Traceable and auditable is important.
It's also important to remember, you know, this pricing data and these outcomes of claims are, you know, there is frequent litigation.
... around claims outcomes. The reliability, and defensibility of those pricing estimates is of high importance to the carrier community.
Yeah. Labor point's really interesting too. I hadn't thought about that.
I mean, very opaque, I would imagine so.
It, yes, it is.
Yeah. There, I would imagine there's a lot of value you can.
you can drive in that.
Maybe to the detriment of some of the servicers but, you know, maybe a more honest assessment of
that.
You know, just last month I was at our Elevate.
That, that's not a fair way to put it. More accurate, I don't wanna say honest. You know what I mean?
Yeah.
You know, just last month I was at our Elevate conference in Utah which brings together the different groups in this community. You know, with Verisk conference as a central point, and they talk consistently about the value of that ecosystem, and then the value of the third party solutions that are adding value to the platform from them.
Maybe talk about, you know, fraud a little bit more. I thought some of the points you made on, oh, I guess we'll call it the photo repository, right, and how it's contributory and very much a network effect. Yeah, maybe elaborate a little more on fraud.
Yeah. Our anti-fraud business on our claims side is a great business. We help carriers identify or flag which of their claims should be further reviewed for potential fraud. We are going to put out a study soon that took a look at the prevalence of fraud in the insurance industry with AI-based tools. Unfortunately, it is increasing the ease with which
Fraudsters can submit or can falsify claims that they are submitting in fraud. One of the things that's shocking in some of our research in the studies is about one in three consumers view it as okay or not a problem to alter a photo they are submitting to their insurance company to support a claim. Which, you know, then can very easily lead into fraud. Our anti-fraud database which has historically always been, you know, the leading place for insurers to review fraud claims and be able to identify the single biggest predictor of fraud is quite simply what is the prior claims history of that.
Claimant, whether it's an individual or small business. The contributory database helps them identify that.
Now that was our historical strength. We are moving into the future with new technologies and AI to be able to identify the more, you know, the more modern fraudsters. We have built what's called Digital Media Forensics which now helps them identify if there is a photo submitted.
with a claim, has it been digitally manipulated?
you know, does it appear three years ago in a different claim and somebody's duplicating the photo?
We have built up in this a data set of over 600 million images contributed by the carriers. It has contributions from at least five of the top 10 carriers and growing by the day. This we think is just a perfect encapsulation of the fact that as technology develops, carriers are seeing more value in the contributed, in what they can
get from the contributed data sets that Verisk can bring to the table. We are creating, you know, more data sets not less, and bringing, you know, more value to the industry, in this case in identification of potential fraud.
Okay. What keeps the other five from not joining? It seems again the contributory network effects why not be part of the-
We're working on it.
Okay. Fair enough. You know, another focus for the Investor Day was using AI-enabled automation to lower your internal cost structure. As you're you know, deploying whether it's GenAI or generative AI, you know, how do you ensure those efficiency gains you know, flow through to the bottom line, you know, aside from maybe being competed away? I mean, you already have very high margins, so yeah.
Yeah. Yeah. In terms of making sure that we have efficiency gains and not competing away, you know, fundamentally that gets at protecting the value of the top line. You know, we've never priced our products to cost. We've never said, "Well, it costs us this much and so you get a 15% markup," or, you know, whatever it is.
We are focusing the pricing on what is the value delivered to customers and what is, you know, what are their alternative ways at getting at the same solutions. If you think about it, from an insurance carrier standpoint, for every dollar they take in premium, they spend on average $0.70 paid out in claims. They spend on average $0.25 of OpEx in running their underwriting and their claims departments.
They, you know, leaving about $0.05 of profit. This is for the sort of operational insurance side of the house. You know, set aside the investment side of the house for a minute. If you think about that, and then Verisk's revenues we said were on average, you know, 30 basis points of the industry premium. Of that dollar they're spending $0.003
on Verisk solutions, you know, system-wide. That $0.03 is protecting the $0.70 of claims.
ensuring that they price each new policy right, that they act correctly.
On each claim's outcome. If you think about pricing a new policy, you come in with a price that's too high and someone else is gonna take the business from you. You'll get competed away. You price that policy too low, and you're gonna be underwater on that.
on that bucket of claims.
It's maintaining the value of that $0.003 is what's fundamental to protecting our pricing, our top line, and therefore our margins.
Right. Hopefully enhancing the profitability of your customers since.
Yes. Exactly.
you know, like a fair value.
We think there is significant opportunity for that.
Switching gears a little bit, you're enhancing your client risk tools, analytics, your catastrophe models. Climate volatility has become a bigger issue, a board issue, right, for a lot of companies. In terms of, you know, a growth opportunity for Verisk, you know, I guess, how would you size this? You know, and how does that, you know, perhaps, expand beyond sort of the traditional, you know, property and casualty business?
Yeah. We think there is potential opportunity there. You know, our catastrophe and risk models are used. You know, we think they're the leading models to benchmark catastrophe risk. The traditional usage is for insurance and reinsurance, for insurers to decide how much of the risk to cede to reinsurers, for both parties to agree on the pricing. It's ultimately the benchmark on which they trade. It is a sticky business in the sense that those decisions, those risk decisions, have implications. They drive through to the capital that's held against those risks.
It has, you know, both regulatory implications for both insurers and reinsurers, as well as, ratings implications, which is very important to them. Those. You know, that's the traditional value proposition.
... of our catastrophe risks. You're right, as increasing climate focus becomes, as you say, a topic in the boardroom, a topic for financial institutions that have exposure to property and catastrophe risk.
Yeah, we do see opportunity there.
Okay. Very good. I think across the information services space, you know, arguably one of the most, maybe the most defensible, you know, set of data assets, right? It's. You know, a very large proportion is purely contributory. There's obviously a lot more built around that's walled off and protected. As you're pushing into, you know, again, you know, newer verticals or, you know, adjacent verticals, how do you incentivize, I guess, early adoption for your customers? You know, historically, I think it's kind of a slow-moving industry, but, you know, how should we think about then just, you know, getting the flywheel spinning quicker, I suppose?
Yeah. It's a great question. I mean, in terms of incentivizing new datasets, you know, we showed some of the stats at our Investor Day of you know number of datasets contributed increasing over the last year or two by nearly 100%. When it is adjacent to our core products, I think that as we demonstrate some of the stats and some of the outcomes to our customers, you know, for example, in our core lines business, we've created more and more benchmarking reports, which can allow a carrier to compare their own outcomes or performance to industry benchmarks. As we see this and we have.
You know, as we have more senior-level strategic engagement, they can get very interested in this and say, "Oh, that's interesting. You know, you can benchmark for me, you know, one line of business in one line of sight, in one state." We've had some of them then say to us, "Oh, can you do this for me in this other line of business?" We say, "Well, actually, you haven't historically contributed-
... that type of data to us." That can incentivize the contribution. The Digital Media Forensics is another one where we've been able to prove out the value proposition very quickly. Because we're already connected to the industry, we can create proof of concepts, or we can prove out very quickly without them spinning up a whole new contract NDA data contribution. We can take the data that we already have in-house from them.
we can say, "Look, with this tool, you could identify $10 million worth of fraud in the past, in your past year. Is that of interest to you?
We can move quickly with that.
that gets the flywheel spinning.
That gets the flywheel spinning.
Yeah, go on from there. Yeah. Okay. That makes sense. International markets, you know, historically, you know, a smaller piece of business for you versus domestic. I guess, how critical are non-U.S. markets in terms of achieving your long-term growth targets-
Organically?
Yeah. You know, we're
through inorganic growth.
Yeah. We're comfortable with the portfolio we have. We're very comfortable with our current, you know, long-term growth targets of 6%-8%. We do have some businesses. I mean, today, international revenue is about 17% of our total.
You know, quite a bit of that comes in our catastrophe and risk modeling.
business, which is obviously a global view of risk and has global customers. More generally, I think, you know, we have a strong presence now in the U.K.
between our Lloyd's market business and then
Our some general insurance and claims businesses. I think as we achieve critical mass in those markets, we continue to see opportunity to sort of densify, but this is not an environment where we need to go out and.
you know, plant a flag in different countries around the world.
Continent of Europe, is that much of an opportunity?
It is a bit of an opportunity, yeah, and in the past three-year cycle, we've acquired a couple of businesses in Germany.
Focused on the claims side and building us to a position where we are sort of the only independent claims technology business in Europe in a market that's fairly concentrated with some high-position carriers.
I guess how do the data repositories, the data sets, you know, the contribution models differ from the United States? Is there a corollary there too?
Yeah.
We would love to have contributory data businesses.
All over the world. It's a great business model. For structural reasons,
It's difficult to achieve.
Because of the founding of the company. Yeah.
Yeah. Yeah, obviously it goes back to the foundation of our company in the U.S. In many other international markets, either there may be a nonprofit, you know, player already.
Look, the need for the contributory data set in the US came about because of the fragmentation of state-by-state regulation, which doesn't-
really exist in other domestic markets.
The lack of concentration in the overall insurance industry.
I see.
Many of the markets in Europe have, you know, they don't have that state-by-state regulation phenomenon.
They have more concentrated players.
What we're doing in Germany is a little bit of an alternative view to that.
Okay.
Structurally different, right?
Yes. Yeah.
EU doesn't, you know, mean U.S. Okay, it's just yeah.
Okay. I understood that. That makes sense. Product velocity, innovation, another, I think pretty important focus.
Yes.
Structural changes you made internally, right, to ensure, you know, your new analytical tools I guess come to market quicker and ultimately are adopted by your customers?
Yeah. I mean, I'll start with the simple structural tool, which is that we had a bunch of businesses in other verticals.
We divested those. The structural simplicity of being an insurance-only focused business and insurance-only focused leadership team.
meant that all of our capital was, you know, either invested in the insurance business or returned to shareholders. That, I think, you know, accelerated the focus on what we could do.
and accelerated, you know, the resources that we were deploying on it. That's point one. Point two, we recognize, you know, this has been gradual, but in 2022, we definitely doubled down on the moment in time that we were at of the insurance industry really needing more modern digital tools.
which Verisk was in a unique position to provide because at the end of the day, that's why we were created, to help them bring better data and analytics to the table to better select the right risk, price the right risk, and combat fraud. That's why we were created in the 1970s, but in the 2020s, there has been a unique opportunity to do that. That was abundantly clear, you know, throughout, but particularly even in 2022, you know. Before ChatGPT launched and every conversation started being about AI, we were already on this path of investing in the digitization, and better data and analytics and tools for our
For our customers. I think that focus is what drove the product acceleration over the last three years and which we think can continue. You see it manifested in our financials and in our results, whether it's the acceleration of our subscription revenue growth to be north of 8% in the last three years, or whether it's in that product inflection. We measure the number of products per customer depending on the size of the customer as a way of assessing our, you know, land and expand.
What some people call it. That has definitively inflected upwards over the last three years.
Maybe looking at it from the And I'll use a comparison, looking at it from the customer side and thinking about kind of rate of change and you know adoption of more sophisticated technological tools. You know, a couple sessions ago, Steve Hasker was talking about how they've dramatically increased you know the number of you know AI centric tools, but they're kind of ahead of the curve in terms of you know rate of adoption by their customers. Maybe a corollary to the insurance agency. You know, in terms of willingness, need, you know or just kinda rate of adoption for your core P&C clients, you know, where does that sit right now?
Is there still, you know, a good amount of friction because of, you know, there's, you know, slow to change industries, I suppose? Yeah, where does that stand?
Yeah. I think, yeah, it is a journey, and you're right, the industry is, you know, takes a cautious look. You have to keep in mind it is a regulated industry.
Highly regulated, yep.
Highly regulated, focused on risk, and required to bring, you know, auditability.
Defensibility. Remember, insurance claims are some of the most litigated contracts in the world. So if they say, you know, "Your premium is X," or, "Your claim was Y," and, you know, they need to be able to back that up in any potential lawsuit. So, you know, so that's one element of it. I think you're seeing. Clearly there is an appetite for modernization and appetite for more efficient work. I think there was an adjustment period where many of them. You know, we led on sort of the AI governance side of things. We put out an ethical AI policy very, you know, very early on our website.
We have established an AI governance board very early on to review for each model, for each product that we build, what are the potential risks? How is our IP being protected in this? You know, are there any potential data risks or protections? We review that very carefully because we view it as doing it on behalf of the industry.
With that trust on a solid foundation. I think our customers are interested in taking on products. You know, they themselves then had to establish their AI governance boards, and they may have their review processes.
You know, in some cases, it may mean a slightly longer sales cycle as they review things.
You know, we always have dealt with kind of.
long sales cycles.
nothing new for us.
I would imagine that's a moat as well.
Yes. Yes.
Fair enough.
Yeah. That's been good. Look, large companies in the insurance industry is doing quite a bit with AI on their own.
That doesn't replace what they are doing with us. If you go back to that economic model I described of the $1 they get on premium, $0.70 on claims, the $0.25 that they spend on OpEx, that's their target.
The things that they do internally and operationally, the $0.003 that they spend with us for better data and analytics is not gonna be their first target to replace. If they tried to rebuild that.
It would cost quite a bit more than $0.003, not just once to transition.
on a permanent and ongoing basis.
Yeah, that was sort of the next natural question. You know, are you seeing, you know, some of your larger clients trying to do this?
Trying to do what? Trying to use AI?
Absolutely.
To internalize-
100%.
You know? Yes.
Yeah. To replace what we are doing.
Yes
For them, we are not seeing that.
Okay. Okay. I guess, you know, one of the more common questions I get, just thinking about sort of the growth arc, you know, aside from just general pricing and new product adoption is sensitivity to either net written premiums or just overall industry profitability, which can be volatile. I guess in terms of just, you know, answering, I don't know if it's insulation, but maybe sensitivity to those things and you know, ultimately pricing power, you know, how would you answer that, I guess that question?
Yeah. You know, we have historically grown faster than the insurance industry net written premium growth, but much more stable through the cycles.
If you look since 2009, because that's when we went public, so that's when we have public financials, insurance industry net written premium growth on average was about 5% during that cycle.
Our insurance business organic constant currency revenue growth was about 7% on average, but the variability of the insurance industry.
It ranges from, you know, negative growth in some years to hitting double digits most recently. Wider dispersion. Verisk's growth has, you know, been 6%-8% basically in that, or between 6% and 8%, so a much tighter band around that 7% outcome. Actually, if in that time period, if you look at the years that were soft markets from an insurance industry perspective, versus hard markets, during the soft markets, low premium growth, Verisk's average revenue growth was 6.8%.
If you look in the hard market years, Verisk's average revenue growth was 7.3%.
Little bit of a headwind and the, you know, little bit of a differentiation between those, but it-
They kinda still both round to seven.
It's a band.
Yeah.
A pretty tight one.
It's a band.
I would imagine at least a decent bit of that is just the consequence of contract pricing, right?
Sorry.
Well, being on contract pricing, right?
Yeah. Yeah. Okay.
Longer duration contracts that kinda ride through, and that gives you the.
Okay. That makes sense. Yeah, I guess in a similar vein, right? Elizabeth, you I think started your tenure in 2022, a lot of change, kinda getting back to the basics, and I mean that in a very good way. Pure play company, you know, big market, you know, clear need for what you do. When you're meeting with investors, and I'm sure you've spoken to a lot of them today, what do you think is still misunderstood, underappreciated, you know, about, you know, Verisk market position, growth opportunities, however you wanna answer it?
Yeah. I think two things. We, you know, we just touched on, you know, one of them is the premium-
There's a near-term bias of we're coming off, you know, 2, 3 years with very strong premium growth. There's a sense of, oh, if premium growth is coming down, then your revenue's gonna come down. To me, one of the charts that we had in
Investor Day shows, you know, from a longer-term historical view, this is just normalizing to an industry average, and we have sustainably been able to grow above the industry. Maybe a modest headwind, but not something that we are significantly concerned about.
The second topic that we've touched on a little bit here and that clearly I've spent a lot of time talking about obviously is the AI question.
I think it's important for people to understand that AI can enhance what we are doing for customers. It can enhance what the customers are doing themselves. The defensibility of our business relies on the value proposition that we're bringing to the table. The businesses that we have, and that we go to market with, these are not generic workflow tools.
These are not, you know, just some sort of random analytics or piece of.
You're not a workflow platform.
We're not a workflow platform. If you look at, there was a pie chart in our Investor Day that showed our revenues in terms of defensibility to AI. We had, you know, 40% of the revenues come from contributory data. 20% of the revenues are built off of proprietary data, 25% are built off of proprietary IP and analytics that generally rely on that proprietary data.
You know, 10% from software, 5% from services.
The 85%, you know, the 85% of that business maps to essentially our five largest businesses.
which each have in their own way, a distinctive value proposition for the customer set.
... that we think will continue to prove out our products can be modernized with AI, and what the carriers want to do with AI independently will not replace the value of those, you know, five strong businesses.
Very good. Maybe just pause for a second if there are any questions just from the audience. Happy to take them. Otherwise, we can go on. Cool. All right. Two ones. One just on capital allocation and the next, just do a lightning round of word association.
Recently announced a large authorization $2.5. I think you've or going to execute on $1.5. Seems like there is a maybe you could say a shift in terms of where capital's going and maybe given the valuation, but I think that probably makes sense. I guess how do you weigh that, you know, again, in terms of you know the accretion from that, the level of buybacks and then just you know weighing and you know being able to pounce on you know that whatever the next you know big opportunity or opportunistic opportunity.
Bolt-on, right?
Yeah, I think, look, we're fortunate to have a cash generative business. Yes, you know, our capital allocation framework will look, you know, at any given moment in time, where is the opportunity to drive the greatest return. Obviously, at the Investor Day, we kinda gave the framework of the organic investments, the M&A, the selective M&A and the return of capital to shareholders. The organic investment portfolio we feel very good about. We're driving strong returns. We showed some of the roadmaps coming there. You know, we've funded that CapEx, you know, roughly in line with where we've been spending it.
We're very happy with those opportunities. We have a lot more ideas than what we're funding, so there's more there.
From an M&A standpoint, we will, you know, continue to look in the markets, particularly when there are valuation dislocations in an environment like this.
Our priorities, you know, first and foremost, we are still focused solely on the insurance industry as we have been since.
2022.
We look for proprietary data sets, whether acquiring new ones or enhancing our own, expanding into new insurance markets, new customer segments or new types of risk. Third, bringing you know efficiencies and automation to our clients is kind of our priority set. You know, in terms of things of scale, we will continue to look at, we will continue to be open in the markets, but there's you know we don't see a significant need from our
from where our portfolio is right now. In a dislocated market, we also see the opportunity of returning capital to shareholders.
Right. Yeah, at the right valuation, you know, core business.
Yes
Nothing crazy. That makes total sense. Okay, word association. Life insurance.
Growing.
Growing. Okay. Workflow tools.
Evolving.
Evolving. Okay. Product velocity.
Accelerating.
Accelerating. AI.
Opportunity.
Opportunity. We touched on this a little bit, but, M&A in one word.
Selective.
Selective. All right. Very good. Cool. Elizabeth, really appreciate it. Thank you so much for the time and pleasure.
Thank you so much.
Thank you.
Thanks everyone. Appreciate it.