Verisk Analytics, Inc. (VRSK) Earnings Call Transcript & Summary

All right. Hello, and welcome to everyone joining the webcast. My name is Andrew Nicholas, and I'm the research analyst covering the information services, consulting and HR technology sectors here at William Blair. Before getting started, I'm required to inform you that for a complete list of research disclosures or potential conflicts of interest, please visit our website at williamblair.com. With that out of the way, I'm very pleased to welcome Verisk's CEO, Scott Stephenson, to our Virtual William Blair Growth Stock Conference. Thank you very much for joining us, Scott.

Pleasure, Andrew. Thanks for having me.

Happy to. So just to get people's feet wet a little bit, I was hoping you could just start us off by taking a minute or 2 to give a quick snapshot of the business, just so that everyone on the webcast is on the same page. And then from there, we can move into some of the more specific topics relevant to the current environment.

Right. So I'm going to start with an example of one of the many, many solutions we have inside of the company and then sort of fan-out from that real quick. So if you all have -- if you all own a home, or own a car, and you have an insurance policy on that home or car, the first thing to note is that if you actually look at the bottom of the policy itself, it's very likely to say, "Copyright ISO." That is us. So something that we have done for a very long time is to essentially construct the industry standard insurance product. And the reason that we do that is because our customers will follow us -- follow behind us as we go to regulators. The regulators approve what it is that we have structured as the insurance product. And then our customers can come behind us and say, either I'm doing that program that comes from Verisk or I am doing something which is the same program, except with the following differences. And also, you're going to quickly move towards approval. So there's a whole interaction with the regulatory process. That was actually how the company got its start in the world. But sort of moving forward from that, so let's say it's 6 months later, and you have sustained damage to your home or your car. This is what will happen. You will file your claim. Your insurer will go through a process called adjudication to determine that they consider it a legitimate claim, not that they've agreed to what you're claiming, just that it is legitimate that you were making a claim. One of the very next things they're going to do is to take the information. And everything I'm about to describe is machines talking to machines, no humans. What your insurer is going to do is abstract some of the key data out of your claim, send it to us more or less in real time. What we will do is then take that claim and analyze it in the context of about 1.5 billion other claims. And more or less in real time, send back to your insurance company, a signal, which you can think of as here's the last 10 claims that came into us. Yes, yes, yes, no, yes, no, et cetera. The yes is being -- there's no reason to be concerned about this claim. And the reason why insurance companies want that indication is because they actually want to pay your claim in a timely way. They consider that part of your satisfaction and their obligation. But if there's something about it, which hints at potential fraud, they don't want to pay it. And in fact, they want to sort of pull it out of the flow and give it special attention. We are the heart of the insurance industry using big data, data analytics, to try to suppress fraud in the claims flows. We have hundreds of solutions like that, but what is essential about our business model is that most of the data that we've got comes from our customers. And in most cases, we're the only ones that are receiving these data sets. And as a result, we're able to do very unique things for our customers. And that kind of sense of unique data sets, highly automated, very analytic, is essentially -- we've got many, many solutions in the insurance industry, in the energy industry, which includes oil and gas companies, electric utilities, companies that produce the renewables in the wind and solar categories and the financial services industry, particularly retail banks. So that is kind of the essence of who we are. And the way I like to describe our business is that we are vertical data analytics. So we exist inside specific verticals. There are 3 in particular, I just named them. We don't try to be everything to everybody. But in the verticals that we serve, we look to be the industry standard as it relates to this kind of analytic object and analytic environments.

That's very helpful. Maybe we'll start with insurance of the 3 verticals and dig in a little bit there. You typically talk about the 3 different legs to the stool, let's call it, between cross-selling, pricing and new product innovation in that segment. Just kind of curious with -- given the environment that we're in, kind of how you're thinking about each leg of that stool? And how the health of your client base is impacting your actions at the moment?

Yes. Thanks, Andrew. So I would report that the insurance companies, in general, are in good shape. If you think about a couple of the implications of the COVID-19 moments, one of them is the macroeconomy has taken a step back. So in what ways does that influence an insurance company? The primary effect that we have seen of that has been that the rate of usage of automobiles is down. There are many fewer miles being driven. Fewer miles means fewer accidents and so fewer claims. And we can see this trend very clearly in the data. The effect of that has been, you would think it would actually lead in the direction of insurance companies becoming more profitable, but they have realized that they need to keep faith with their customers. And so they have proactively gone to their customer bases and said, that premium that we were -- we had charged you for this policy is now reduced. And not in a way that has fundamentally shifted their profitability, but they're kind of re-rating the insurance policy based on the fact that there's just less usage of the vehicles than was anticipated when the policies were put out. The other thing that people have been watching for is, obviously, a lot of businesses have been interrupted. And there is a category of insurance, which is on the commercial side, which is called business interruption insurance. And we know a lot about this because we actually author the policy language, that description I gave upfront, going before our customers to the regulators. And basically, the -- just the fact of the matter is that if you were a company that took out business interruption insurance, it is clearly stated in the policy this does not cover pandemic-related interruption. Now that doesn't mean that some of the insureds aren't going to complain or maybe try to go to courts or ask regulators and/or legislators to say, "Well, but it really should. So can't you sort of pass a law that says it should?" But that's the fact of the matter and we don't believe that this is going to be existential for insurance companies, not at all. And so the industry is actually in, I think, solid shape. Their overall premiums are not going to come out in 2020, where they would have otherwise because they have done this proactive essentially rebating of premium to some of their customers. But in terms of the profitability of the insurance companies, pretty strong. The one factor I would pull out here is the large established main brand insurance companies that you're all familiar with. What I just said is their condition. There are some of the so-called insurtechs, the much smaller insurance companies, newer, more thinly capitalized. A few of those are probably under pressure. Although I would note that just, I think last week, one of those insurtechs, Lemonade, just went public. So -- but the overall report is that the industry is really pretty strong. So our discussion with our customers and the things we do to add value to them is essentially unchanged in this moment. I mean we can't go to their offices right now, obviously, but we are spending time with them. In fact, we've actually had more contact with our customers over the last couple of months, just if you count individual discussions. We've actually had more over the last couple of months, which is good. And then the other thing I would just report is they, like a lot of companies, have just tried to figure out, well, okay, how impactful is this? And like a lot of companies, it probably has slowed down new buying decisions a little bit, not a lot, just a little bit. And that also we see as a temporary effect.

Understood. I think that's probably a good segue into just the types of opportunities or impacts that you're seeing in the near term on the product innovation front.

Yes.

Are there any -- and I can kind of think about this in 2 ways. One, on the product side, but also just on the behavior side, just effects that you're seeing as a consequence of the current environment. And whether or not you've made any material change in the way that you're prioritizing investments based on what you've seen to this point in the second quarter?

Yes. Last question first, Andrew. No. No change in the program of investment. It's at the same rate and it's on the same things. We build these long-term views of where we think our customers are going and where they need us to go in order to anticipate their needs and give them what it is they need, not just today, but into the future. So no change there. And I think the effect of -- the enduring effect of COVID-19, above all else, will be to encourage all companies, not just our insurance customers, but our banking customers and our energy customers to become, what I refer to, as the better digital version of themselves. If you felt any grinding of the gears as you had to go virtual and remote, then you just know that you don't want that to happen again. And the way that you avoid that is having a very digitally platformed business, a very agile technical environment, which is almost certainly going to include a lot of cloud computing and to be more data analytic so that you can anticipate and respond to things even better. So I think that will be the enduring legacy of the COVID-19 moments. But otherwise, I have the opportunity every year to visit with probably 30 to 40 insurance company CEOs who are our customers. One of the things I dislike about the COVID -- many things I dislike about this moment is I can't actually go see them at their offices because they're great. They're always great encounters. Our customers are very nice to consider us a key business partner, and we work hard to earn that. But what I was -- the reference to them is, I think, out of any 40 insurance company CEOs that I go visit with, 40 of them consider their company to be a growth opportunity and that their goal is growth and faster growth than their peer competitors and the industry overall. They all see it the same way. And that leads them to a couple of things. One of the things that leads them to is wanting to be very sharp in anticipating where is risk going? And what are the categories that are emergent that they can try to get in front of? And often, these fall into what are called the intangibles category. So business interruption, cyber risk, reputational risk, things like that, which are not really all that insured today. So that's part of where their thinking goes. And so a company like us that creates data sets around these things and understands them actually can contribute a lot to somebody that is thinking about getting into these lines of insurance. So that's one implication of that orientation. And the other is more generally, they see themselves as fulfilling their goals to grow primarily based upon methodological improvement. So if you think of something like underwriting an insurance policy, it is fundamentally about data and analytics. I mean that's really what it is. You're trying to get enough information to anticipate where might loss occur in the future, but also to differentiate where the loss occurs, et cetera. And so you get to -- out of that, you would select risk and then anticipating the range of outcomes, you would come up with a price for bearing that risk. It's all very analytic and it's all very data-driven. And they know that if they're going to grow, underwriting is very, very important. And then they want their methods to be great. And that's why things that we do like our LightSpeed platform are so meaningful. And has really -- had a really good track record of growth.

Absolutely. And I would imagine some of those same desires for growth are present in international markets as well. So that's my segue into asking about the international expansion opportunities that you see in the insurance business. My understanding is that insurance in these markets can be localized. It's market-specific type businesses. But you've had some success building up your presence in the U.K. over the past several years through M&A. Just on that topic, do you see opportunities to continue building the U.K. business? What might extensions of your current footprint there look like? And are there any other regions that we should be kind of keeping an eye on in terms of what's most promising to you in terms of future expansion?

Yes. So first, a comment about what at least so far has not been a part of us being interested in global markets or globalization. And that is -- it is interesting with the exception of reinsurance, how local insurance really is. In other words, there are very few of our customers that are headquartered in the United States, and that grew up in the United States that have done anything, which is particularly meaningful or large outside of the United States. It's just an interesting thing. And I can think of reasons why that is, but that's just the case because the most natural thing would be for us these great relationships we have with these companies to just travel with them as they travel into these other markets, but there actually is not a lot of that. And so instead, what we have to do is become relevant and meaningful locally. And so we picked the U.K. as the first major market language through the obvious reason. A not small economy, not a huge economy, and an economy with some relatively sophisticated insurers which we felt is the right environment for us with our advanced -- the advanced kinds of things that we do. It's worked very well. It's been a combination of -- we did buy some small platforming kinds of companies that had local customer base and data sets related to the U.K. market, and that was the way of getting started. More recently, we've moved into a theme which is more a part of our company over the last couple of years. And that is SaaS platforms basically, which -- and maybe, Andrew, we'd like to talk about that. There is this kind of closed relationship between vertical data analytics the way we do them and vertical SaaS that we can talk about that. But anyway, we see that relationship. And so we have also both bought and built SaaS platforms related to those markets. And we've just become a different animal in the U.K. over the last 5 years. We just have profile and standing that we didn't have before. We had good relationships and we had business, but we're just kind of different at this point. And so the logical extensions for us are -- what we do generally is going to be adopted more rapidly in an established market than in an emerging market. We've just received a lot of feedback in emerging markets that what we're doing is just a little too advanced. It's just a little too high powered. It's just a little too much beyond where they are today. But in the established economies that have mature insurance markets, there's an appetite and an ability to recognize what we're doing. So Mainland Europe definitely makes sense. We've actually got a nice book of business in Japan and interested to try to grow that as well, as well as South Korea and Southeast Asia. Singapore is a pretty big location for us. So -- but the way that we think about it is we want to actually aspire to critical mass, have a number of offerings across the insurance value chain, and that's what we're working on. And we're not nearly done building that out even in the U.K., which is where we've done the most so far.

Sure. And I think another example of this kind of vertical SaaS approach is in your acquisition of FAST.

Yes.

So I'd kind of like to use those comments and segue into that acquisition.

Sure.

How that kind of help extends your capabilities in the life insurance segment? And what kind of opportunity that could be and maybe what some of the differences are in that market versus where you typically used to play?

Yes. Thank you. Yes. So exactly. So starting with the theme of vertical SaaS. To the extent that we're going to use an M&A dollar to try to give us access to a domain that we're not in. One of the best ways to do it, in our view, actually, is with a well -- a leader in a category which is being served in a vertical SaaS mode. One of the things about those kinds of businesses -- or let me make a general point. Here's the general point. Our company started out -- there's a spectrum. At one end of the spectrum is what I would refer to as content richness. So you're in a domain, you're in a vertical. And the thing about you in trying to serve the companies in that vertical is that you have a great deal of content. You have data, data converted into analysis, which is very specific to the domain and very relevant and very valuable. That's one end of the spectrum. The other end of the spectrum tends to be the software-intense business models, which are about, again, trying to enter into the life of the companies in this industry. But the way of doing it is a software basis to try to work on process, often process that relates to either decision-making or transaction processing. And at that end of the spectrum, what you're starting with is this helps you to work more effectively. And at this end of the spectrum, it's -- we can give you a perspective and insight that is different than what you have. The point I wanted to make is, if you start out content rich, we've seen this over and over again. If you start out content rich, generally, the direction of travel is going to be towards more software intensity. And if you start out software intense, the second act is almost always to try to become more content rich. Two comments about that. One is, if you made me choose between those 2, I'd rather start out content rich because you're instantly relevant. But in some cases, we don't have that option, but we can start out with the software intensity. That's the vertical SaaS. That was -- and so that was part of the motivation behind FAST. And then the other part of it is, we went through an analysis comparing the life insurance market to the P&C insurance market, which is where we got our start and where we have built a large book of business. And we saw 2 differences. One is, in the life insurance market, there, we just didn't see any 800-pound gorillas providing vertical SaaS that had -- were just sort of be inevitable. Of course, if you're going to buy, you're going to buy from them, kind of a thing, one. And two, really, the quality of the data analytics solutions in the life insurance space, up until now, have just been so much less valuable. P&C is just a lot more complex. And so P&C has been working on complex analytics for a long time. Life insurance really has not. It's just simpler. But we think that we can bring our analytic capability and make a difference. So we have showed up. Our theory of the case was that FAST had the best vertical SaaS and was making progress, but it's an enterprise-level application. And so customers were probably saying, yes, but are you going to be here 5 to 10 years from now? Because if I'm going to bet on you, I need you to be here. That question seems to get settled now that they are owned by an S&P 500 company. But the other part of it is we're also supporting that with Verisk's analytic capabilities and that's different than what's in the life insurance industry right now. And the combination of those 2 things, the influence of a really established player that knows the insurance environment and bringing our analytic capabilities, we've actually had tremendous sales success since the acquisition. We reported on that to a degree at the last earnings call. So that's the theory of the case. And I'm really pleased that it seems to be bearing out in the first few months of ownership of FAST.

Perfect. Perfect.

I'll note also, by the way, that globally, life insurance has more premium dollars than P&C. It's actually bigger.

Would imagine it's a huge opportunity. So just -- I'm looking at the clock, I want to make sure we get to some of the other segments here. So maybe moving on to energy for a little bit. Certainly a choppy time right now. I guess, before getting into the impact on your various businesses, I was hoping you might just comment on the industry as a whole, broader impact of the current crisis on the industry, and how you see this playing out over the next 6 to 12 months to the extent that's a fair question.

Yes. It is a fair question. So first of all, when we talk about energy, I just want to highlight the range of kinds of customers that we serve in what we call the energy vertical. So we work with the integrated global oil and gas companies. We work with the pure-play exploration and production companies, and there are a lot of those especially in the United States. That, by the way, is by far our smallest customer segment. And that is the segment of all the ones I'm about to describe that has been beaten up the most, but we have actually relatively little business there. That has not really been any material part of what we do. But that is -- that's out there. They are national oil companies. They will always be around. They create revenue for their governments. They really matter. We work with electric utilities. We work with people who trade in terms of energy and energy commodities. We work with the petrochemicals business, which is all the way downstream. And everything that's between like refineries, for example, and then the ultimate petrochemical products. So that's all of -- and we work with investment banks who advise all the companies that are thinking about buying or selling or trading assets. So all of that is in our customer base. Fundamentally, the -- and we also work -- excuse me, we also work with the companies that work on the renewables, wind and solar. Fundamentally, the world is hungry for energy. The world's population is expanding. Economic activity expands not last couple of months, but it does. And so all of that implies the need for more, not less energy. And so whether it is coming from a hydrocarbon or a renewable or what have you, this sector is really important. And that's part of our thesis, which is it will always be important. And also understanding the way that the energy sector interacts with the climate system, which is something that we know a lot about because we model the climate system for insurance companies. That is -- we think that is a powerful set of capabilities against a very large need. And then the other thing I'll just say about the energy space is as large as these companies are and as much data of a technical nature that they generate, they're actually -- of the 3 verticals we serve, insurance, banking and energy, energy is the least developed by far in terms of harnessing data analytics to make commercial decisions, by far. And so we feel like bringing what we're good at into that world is very meaningful. Just one other comment. I know we're running out of time, Andrew. A lot of what happens in the energy space ultimately delivers as a commodity. Commodity cycles -- or commodity products have cycles that insurance doesn't have, and actually, retail banking doesn't have. And so there is the opportunity for sort of up and down in terms of the state of the industry. And it has a temporary effect, but we think the long march is an energy-hungry world that is trying to figure out how all of these different parts play together. And we feel like we have a lot to add to that. That's why we're in the space.

No, it makes sense, and that's a good point in terms of the progression of data analytics in that vertical versus the others. I think we have a minute or 2 here left. Obviously, there's many questions I could ask. But maybe one that helps kind of wrap this up a little bit. Fast forward 5 years from now, and it could be something that we've already talked about. But what's the one part of your business you're investing in today that you're most excited about, 5 years from now being a really material growth contributor? I'm thinking about things that are a little bit on the smaller end now, but anything that comes to mind or off the bat and how you're thinking about that opportunity?

Yes. Well, there are several things. And I think your question, Andrew, goes into sort of product space, so I'll start there, but then I'm going to make an additional comment. So on product space, I am really interested in all the things that we have that support players in the energy space, understanding and moving into what's called the energy transition -- sort of the rebalancing from hydrocarbons towards other sources of energy. Bearing in mind, by the way, that most predictions say that 20 to 30 years from now, we will be using as much hydrocarbon as we are today because an energy-hungry world can't move but at such a rate in terms of getting somewhere else. But all of the things that we can do to contribute to the energy transition, those are -- we think that those are really, really great opportunities, and will really lead. Another category that we are very excited about is taking all of our spend analytics, which grow up in the banking vertical, but converting them to be of use to everybody else to understand spending patterns and then draw conclusions about how to promote products, et cetera. We have a book of business there today, not as developed as we think it will be. And a third thing that I'll just sort of call out here is there really is a lot of opportunity for applying basically machine learning and artificial intelligence to the underwriting process in the insurance industry. And that is something that we do, do and we invest in and I believe will be material in terms of our performance going forward. And then just I -- very quickly, I know we're running out of time, but I just wanted to take that and rotate it 90 degrees and say, there's a whole stream of investment we're making in methods. Ways to tokenize data, ways to create data fabric that everybody across the company can make use of. We make these investments in the center and then they're available to all parts of the business. It's kind of like if you were in the steel business, you know that reforming and improving the way that you make steel can have something to do with your commercial result. It's not just technical. It's like you get to a different place where you can make it faster or you can make it more inexpensively or both, and then now you're different than everybody else when you go to market to sell. All these methodological things, harnessing the cloud, getting off the mainframe, these will all help us to be that much more agile and fast and useful to our customers. And so I just didn't want to miss that because there's a lot of investment in that way also, kind of like once in the enterprise and then it works across all the different parts. That's really big.

No. That's perfect. It answers the question. I didn't have time for about some of the benefits of the tech transformation. So we killed two birds with one stone there. I think we are out of time. Scott, thank you very much for attending.

Pleasure.

I hope you had a good set of meetings today. And thank you, everyone, on the webcast for your time. Have a good rest of the day.

Thank you.