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

Hi. I'm Jeff Meuler, Baird's Information Solutions analyst. This is the session for Verisk Analytics. Verisk is a leading provider of vertical data and analytics solutions primarily to the insurance industry as well as the energy and financials industries and some others. It provides a variety of truly must-have solutions to almost every major company in the end markets that it serves. With us today, we have the company's group President and CFO, Lee Shavel for the conversation. Lee joined Verisk as CFO in 2017 and was promoted to Group President earlier this year, taking on operational oversight for its energy and specialized markets businesses and financial services segments, in addition to a CFO responsibilities. Prior to joining Verisk he was the CFO of NASDAQ. And previously, the Americas Head of Financial Institutions Banking at BAML. And then also with us doing meetings throughout today is the Head of IR, Stacey Brodbar. But to kick it off, Lee, can you start just with a brief overview of what does the company do? Any common business model characteristics between your segments and a few financial metrics so that as we go through the conversation, listeners know the relative significance of each segment in your overall growth targets.

Great. Thanks, Jeff, and thanks, everyone, for joining. I want to say it's a real pleasure to be here at the Baird conference. And I really -- we certainly believe, I know speaking for Stacey and I, while I tend not to tell Jeff this directly, we honestly think he's one of the best analysts that we work with, spends a lot of time understanding our business at a fundamental level, and we really appreciate the penetrating insight of his questions. So it's been a real pleasure to work with you, Jeff, and glad to be here. So let me start off and describe in a general sense of what we do. And at a high level, of course, we're a data and analytics business. And we serve very specific verticals, as Jeff has described. Predominantly, the insurance vertical. And within that insurance, it's predominantly been the property and casualty insurance industry because of the nature of their use of data and our role in collecting data and reporting it to regulatory agencies. But interestingly, as the industry has been evolving to adopt new data sets, the life insurance dimension of the insurance industry has created a new channel of growth for us as well as new emerging areas of insurance on the property and casualty side, including cyber insurance, that I'm sure many of you have been -- become more familiar with given recent events in the news. So that has been our historical legacy. It represents, from a financial perspective, approximately 75% of our revenues and about 85% of our EBITDA. So naturally, it's our highest margin business. It reflects a very strong value proposition that we offer to our customers. And that value proposition, I think, is important to understand because it informs how we create value for shareholders. In essence, what it represents is our ability to collect data from the industry as a whole, the insurance industry as a whole. We have 97%, 98% penetration of the property and casualty insurance industry. We take their data on losses, on claims, in a variety of contexts, and then we supplement that with other data that we think has relevance. And then we are able to invest in and add value to that data and return that analytical value to the industry as a whole. Now embedded in there is a concept of industry leverage where we are able to act effectively as a technology partner and an analytics partner to the industry. So for the investment that we make in our data and analytics, we're able to generate a very high return by monetizing that across the entire industry and with the benefit of the data sets that they, in large part, provide to fuel that. So I wanted to start there because you'll see similar themes in our other verticals. In our energy and specialized markets business, we collect data on a variety of energy-oriented elements: information on petroleum reserves, on natural gas deposits, on solar wind farms -- on solar farms, wind farms. We capture data in terms of capital spending by the energy industry. And we take that data and we build analytical products that we then monetize and sell through our client networks. Our Wood Mackenzie client network, which is our largest subsidiary in energy and specialized markets as well as through our PowerAdvocate base. And we also provide environmental health and safety data through our 3E entity within that segment. That segment represents approximately 20% of our revenues and 15% of our EBITDA. Same dynamic. We collect this broad industry data, and one thing that is particularly important from our view in the energy sector is that as the energy sector is going through this transition from carbon-based fuel sources to alternative energy sources, the interplay between the sources of that power, whether it is crude or natural gas or coal or wind or solar, we are tracking real-time through our Genscape monitor systems and evaluating how it's being utilized from a demand perspective. That has created an integrated need across the energy industry for energy companies, exploration and development companies, power companies, the financial services industry that never existed before. And we believe we're very well competitively positioned to be the leader as a provider of data and analytics services to that industry as a whole, really driving that growth. And we can already see that in terms of the higher growth that we are experiencing within each of those segments relative to our traditional research and consulting businesses. So that's the energy and specialty market sector that I described. Finally from -- the final portion of our business is financial services. This is where we provide -- or we collect a variety of data sets from the large card-issuing banks, which was the foundation of the business. We also collect data on bankruptcies, on advertising effectiveness and merchant dynamics that then we develop benchmarking and other analytical services to evaluate the effectiveness of marketing campaigns. Again, data sets that we are able to invest in, generate incremental value to our clients and create new sources of growth and good returns. The common dynamic across all of these that are -- what I describe as the 2 engines of growth for our business is, one, growing number of data sets that have relevance to our industries. You all, I'm sure, are certainly familiar with the growth in visual data that is available to us, satellite data, social media data, which is a very rich, new source of data on individual activity and behaviors that can be leveraged in a variety of ways. And sense data, the ability to connect information from sensors in a variety of activities, whether it's driving or whether it's tracking, fluctuations of magnetic fields around power lines is creating new streams of data. So as those data sets grow, we have new opportunities to develop. And then the other engine is the demand side, what we experience within the insurance industry, in the energy industry and financial services is growing appetite for automating and informing their activities to a greater extent, and that's what supports us. What finally ties all of this together is that we believe that we can also invest in data analytics techniques, data analytic architecture that is important to be able to develop on a consolidated level. These are our tie-ins to the academic world to leading areas of research that then we can apply to each of our businesses and leverage them more effectively. So that, in total, Jeff, hopefully describes the nature of our businesses, but most importantly the underlying economic value proposition that we offer to our clients and enables us to create value for our shareholders.

Got it. And just to level set for investors, the company targets roughly 7% organic revenue growth on average over time with some level of organic margin expansion, correct?

That is correct. Those are the targets. And I think I may be -- overlooked for financial services, just so you have comparative statistics. The percentage of revenues is about 5% and adjusted EBITDA is about -- the contribution is about 1%. But the targets that you described, that organic growth rate of 7%, is our long-term target for all of the businesses at a consolidated level, but each of those businesses are expected to be able to deliver that level of organic revenue growth. And as you've described, EBITDA growth ahead of that to demonstrate our operating leverage.

Okay. So insurance, obviously, the bulk of the business, a lot of investors love your insurance business, I think, for good reason. And some of them have been wondering why lately, you are a multiple -- multi-vertical information solution company. You just mentioned some of the data analytic techniques or the tech investment that you could leverage across the business. But maybe if you can go more into the thesis behind why be a multi-vertical information solution company? And are there any like common -- or any products that leverage content or data sets across multiple verticals?

Yes. Jeff, absolutely. It's at the core. And let me be clear about one dimension of this, is that while there are technological and operational benefits, we also recognize that these businesses have to demonstrate value creation from a financial perspective. So as I mentioned in the growth expectations, we have to believe that these businesses are able to generate and sustain an organic growth rate at our targeted levels. Secondly, they have to generate an attractive return on invested capital. You can boost growth by being injudicious with capital, so you have to simultaneously achieve that. So we are -- we also track our incremental returns on capital to make certain that they're attractive and also attractive relative to the other opportunities. And then finally, all of our businesses are subject to the test of is this business worth more to someone else than it is to us. And if there is an opportunity to optimize value for shareholders, factoring in our view of value and risk, that is an element as well. So I want to make certain that this is -- the foundation of this is a foundation of financial value. But some of the benefits of doing this are leveraging the technology investment that we've made in insurance and from our other businesses, specifically the financial services. And I'll give you some examples of that. First, from an expertise standpoint, a lot of what has been developing in data science has really been data architecture. How do you tie disparate data sets, particularly of unstructured data together in a way that you can query that data efficiently, analyze it, apply machine learning techniques to it. And so we have, in our Lens project with Wood Mackenzie, have been able to leverage a lot of the knowledge, the technical expertise that was developed in our financial services business to manage the very large data sets that they deal with that we've also learned from our implementation of cloud technology within our insurance business. So that is a structural advantage that we can lever the investment that we've made in that knowledge at the business unit level that we pulled to the corporate level into that business. Also, from a data analytics perspective, things that we have learned or techniques that we have learned on computer vision, allowing a computer to evaluate a photo or a satellite and identify objects of statistical relevance is another area where we can apply that as in the energy sector as we are looking at satellite photos and evaluating oil refineries level of production activity from these entities and tying that into some of the real-time monitoring data that we have from Genscape. Dealing with unstructured data is probably one of the biggest tasks that we have. How do you extract signal out of the noise of all of the social media data that you have available to you? Those techniques are general across this. But what we are able to do is tie that expertise to the specific vertical end cases that we have. And then finally, from a pure data standpoint, something that we've been developing is one data set of relevance for all of our industries, but particularly in insurance and in energy is weather data. We've been analyzing weather for the 50 years that we've been a company in looking at the impact, the losses associated with hurricanes. Our AIR subsidiary models hurricanes and tracks a lot of weather data. We have a business, AER, that provides weather consulting and climate consulting to the U.S. government that we track. We have a business called Maplecroft that analyzes political risk, social risk, environmental risk within various geographies. Those are data sets that have increasing relevance to the energy industry and helping them evaluate impacts, costs and how do they optimize their resources to manage their trip through this energy transition that we're going through. So that's just one specific data set that I would point to, but there are others.

Got it. Helpful. So I want to focus a little bit more on insurance, just given how important it is to the company. You have such a good industry position, so much proprietary data, you add a lot of value for the industry. I guess why is 7% the right growth target? Or why is it the right governor on the business? Like what prevents it from growing even faster because it's pretty consistently been around that level?

Yes. I think there are a couple of dimensions to that. Why is it the growth -- the right growth target? So specific to insurance, I think importantly, it's been -- I think it's a pretty healthy organic growth number for a business of our scale, but it's one that we have demonstrated that we have been able to achieve fairly consistently and certainly on average. There have been some years it's been above, there have been some years that it's below, but I think it's a good base case. And it represents a basic value proposition for what we are doing for the industry. And also, it demonstrates our ongoing penetration opportunity within that industry as we create new sources. I think, Jeff, one of the most common first questions that we get from investors is, how are you able to grow at a much faster rate than insurance gross premiums written basis? And I think it's a failure to understand that we're not tied to the industry growth, but what we're actually doing is penetrating more and more of their operating costs, where our data is used to inform or automate more of that function. We've estimated that our revenues from the insurance industry represent between 25 and 40 basis points. Basis points. I want to make it clear how small that is of their total operating costs, putting aside any losses on the policies. So that gives you a sense that proportionally, that we are still a relatively small impact, but it also shows the potential as we find more ways to apply our data sets to claims processing activity, underwriting automation within that industry as a whole. And consistently, we have found that as these new data sets emerge, or new forms of insurance emerge, it creates new opportunities for us to develop. I talked about cyber insurance. Cyber insurance is a relatively new category of insurance. It is very data intensive, where we're evaluating the defensive, the activities around an individual company's exposure and our ability to tie that data across the industry, build models at AIR that can help them price that is going -- is and will continue to be, I think, a very rapidly growing component for our business. Telematics data that we have been collecting for several years now, and initially, we were ahead of the industry in terms of finding ways to apply it to more usage-based insurance, particularly on personal lines -- on the personal lines auto side is another example of a new development that created new data sets that were of relevance to us. And as we've talked about, the life insurance industry, traditionally, the life insurers would look at mortality tables and price their product that way. But now we have new sets of data that have bearing on how risky of a life peril you might represent. And given that 40% of our customer base also writes life insurance, it's a natural opportunity for us to build off of the strength that we have. I think when we talk about the constraints, there are a couple that have come to mind. One, traditionally has been -- I think there was a -- historically, a view that the insurance business is a great business, which it absolutely is. And there was an opportunity to deploy capital into diversification of other businesses. And we've really kind of changed that mentality to be thinking about where can we generate the best returns in the business, where can we find achievable levels of growth? And hopefully, what you've seen, it may not be as apparent in the internal investment, but I think we have been investing more in these new areas. LightSpeed, as an example, life as an example. So that whereas before you may have seen larger acquisitions and investments outside of insurance, more recently, hopefully, what you've observed is that there are smaller acquisitions that, while not exclusively insurance, probably have a heavier weighting to insurance reflecting some of that capital discipline. So I think that has been historically a little bit of constraint. And as we see new opportunities, we've invested in them. The other 2 constraints -- there are kind of another 3 constraints. One is we are -- to my -- that original guidance question, trying to demonstrate operating leverage through EBITDA margin expansion. And so one constraint naturally is that we could invest more, and I would say, probably at good rates of return, but we are trying to balance our margin -- our margin expansion objective. So that's a constraint on growth. And then, of course, I can't let it pass, but we can also be injudicious with our capital and focus on just investing in high growth businesses without being disciplined around value. That's not going to happen, but that's a constraint. We want to make certain that we're growing, but we're also generating a good return on capital. And then finally, I'd say the final constraint is to a sense we have to -- the industry has to come along. And I would say, on that front, we're seeing more momentum and more interest in analytics and utilizing data to automate more of that industry. Probably 5 years ago, the insurance industry was a little cautious on the migration to cloud environments. Now that is not an impediment. But we do face some level of receptivity constraint within the industry for new technologies. It's naturally a conservative industry, but we feel as though we're continuing to make progress and achieve momentum.

Excellent. And I'd love to ask more about insurance, but I got to get one in on energy and specialized. So you serve a more cyclical end market there, but it's probably a cyclical or a historical anomaly that you've had 2 major end market downturns in a 5- or 6-year period. And I think you've said you just need a normal end market to hit your target growth, but you haven't achieved the targeted growth consistently in recent years. So help investors understand like what does 7% or better organic growth in the energy and specialized business, where does it come from? You said earlier that you have some of these other areas that grow faster than traditional research and consulting. You teased us with energy transition. But just help us understand what the formula should look like to achieve that growth in a more normal end market?

Yes. So -- and I think you've raised kind of the 2 elements that I can talk about in that regard. And one of them is viewing -- looking through some of the cyclical elements of the business. And one component of our business that will continue to have a higher degree of exposure to that cyclicality is our consulting business because it tends -- we tend to see higher levels of consulting activity when we have price swings positively. Now that exposure has come down proportionately as we have developed these other businesses that are less tied to the commodity element. So one aspect of this is that the business -- the business risk over time is going to go down in terms of that exposure. But there is still an element there. Part of what I'm doing is trying to see through the cyclicality to the elements that are more sustainable. And I think -- when I think about these components, with the objective of how do we achieve that 7% organic growth rate, the 2 components that are, I think, are critical are on the core subscription research business, can we achieve a mid-single digits growth rate for that business? And part of that is in demonstrating the incremental value that we're adding through our, Lens platform. And the good news on that front is that as we've introduced that product, we have, even in this more challenging end market, have been able to achieve high single-digit pricing increases for those renewals as our clients understand the value of accessing that data, tying those data sets together and supporting our research. So that's one component that I think is necessary. And then in addition to that or supplementing that in order to get us to that 7% target, we have to have businesses that are generating growth above that 7% target. And the good news on that front is that we're already demonstrating that in our energy transition business, the chemicals business, metals and mining and some other dimensions to the business. And so we are seeing that component shift in that where those newer business lines that are benefiting from the energy transition and their relevance are providing supplemental growth to lift that. Now I'll tell you, that's not terribly dissimilar from what we have in the insurance business, where we have some legacy businesses that are probably mid-single digits growth businesses, and we've been able to supplement that by penetrating and identifying these new areas of growth with new data sets, new analytics. And so in a way, I think we're trying to mimic that. There is more cyclicality that we have to see through. But what we're looking for is the core economics on those subscriptions and those new growth businesses. Hopefully, that gives you a sense of how we think about exactly the equation that you're describing, Jeff.

It does. And just one question on financial services. I don't know if this is your former investment banking hat that's going to answer the question, or if it's the CFO of Verisk hat to your shareholders. But I guess, why is this a good business? It's -- and I'm not focused on Q4, Q1. I'm looking at the last 4, 5 years, it really hasn't performed very well. So why is that a good business that's attractive? And if it is, like what's been the issue over the last several years now in terms of a failure to achieve solid or consistent organic growth?

Yes. And Jeff, thanks for the question. Absolutely fair observations. And so -- and I'm going to tell you, the things that are good about the businesses and some of the challenges that the business has faced that we are addressing. So on the good side, one, this is an absolutely unique data set. What the consortium of banks shares with us is no one else has this collection of data. The card associations have their share of the spend data, the credit bureaus have some of the credit, the credit data, the banks have their demand deposit data, which is kind of a critical tie in what's happening within those accounts. But nobody has it all and has the ability to analyze that on behalf of that -- the card industry segment. Again, that's the industry leverage that we bring to bear off of the data sets that are contributed to us. So that's fundamentally attractive. The other thing that's very attractive is that because of the scale of the data sets that they're managing, they have developed the highest order of analytical techniques and data architecture techniques that we've been able to leverage in other parts of our business. So there is real intellectual capital value within that business that we have. Now some of the constraints or challenges that we have are, one, that it is the bank's data, and so we have to be careful about how we utilize that data, and we work with the banks to determine how we can create incremental value. One area that has been very successful for us has been spend informed analytics, where we're able to look at marketing campaigns, whether it's for credit cards or retailers, in physical geographies, in social geographies and evaluate the effectiveness of that. That's an area that we would like to expand and find more use cases, and we're working on ways to leverage the data sets more effectively on that front. But it is -- one of the constraints has been developing that in a way that is supported by the banks that are contributing that data set. The other constraint is a bit of a historical constraint that we have under our current leadership, has been doing a great job of moving from a very consulting-oriented approach in the business, where the objective was to bring in that new large consulting assignment, leveraging our expertise of the data, that was -- that can be great in terms of generating near-term revenue but it can be challenging in creating sustainable growth for the long term. And that has been kind of fundamentally, I think, the biggest factor that has prevented us from demonstrating the underlying growth within the business. But we have been developing a stronger, more sales orientation and product development function to take what we're learning from the consultants and product ties that more effectively. We've also, of course, been more affected by the pandemic in that sector because of our exposure to bankruptcy volumes advertising reductions at the height of the pandemic, and generally just bank cautiousness from a credit standpoint going into this. So I think our expectation is that as the pandemic recedes, as we begin to see a recovery in that sector. It won't happen as quickly as some of the other more cyclically sensitive players in the space, but we are beginning to see some improvements environmentally in a variety of those businesses. The other element is that the contractual transitions that we've undertaken to move this away from a very front end-oriented consulting business to more sustainable growth over time are playing out in '21 due to contract transitions that occurred in 2020. So that -- we should be through that by the third quarter of 2021. And then beyond that, we'll continue to find areas to develop. Let me reiterate, that same 3 hurdles for this business are, do we believe we can achieve and sustain the organic growth targets that we have for the business? Is it generating an attractive incremental return on capital? And is it more valuable to another player relative to us given what we can achieve? Same tests that we apply to all of our businesses.

Got it. And unfortunately, we're out of time. Thank you, Lee, as always, for all of the insights. There is a breakout session. We'd love to have investors follow us over to get your questions answered. I think you click at the top right of your screen to join us, but Lee and Stacey will be available. So thank you, everyone, for joining. The next formal presentations will be IAA, Novanta, UniFirst, Bentley Systems, Shoe Carnival, Verra Mobility and YETI. Thank you, everyone.

Thanks.