When evaluating the competitive advantage of a data-based analytics business, three important questions come to mind: 1) Is the data proprietary? 2) Are the insights from the data critical? and 3) Does the data fuel a product feedback loop?
Verisk Analytics began its operations in 1971 as Insurance Services Offices (ISO), a non-profit enterprise started by P&C insurers to collect industry data and information that was used by its sponsors to determine premium rates, underwrite risk, develop products, and report to regulators, basically acting as a cost center for the P&C industry. The entity expanded into analytics with its acquisitions of American Insurance Services in 1997 and the National Insurance Crime Bureau in 1998 (which brought expertise in claims fraud detection and prevention) before converting to a for-profit organization in 1999 and going public in 2009 as Verisk (ISO became wholly-owned subsidiary of Verisk). The company acquired a bunch of companies from its ISO days to today, bolstering its core insurance risk assessment services and expanding into new industry verticals.
Verisk’s decades-long legacy as the central repository of P&C industry data is the heart and soul of its competitive advantage and has served as the foundation on which all its other offerings have been built over the years. It is difficult to overstate the critical role that Verisk plays in pricing, claims management, and administrative efficiency across the P&C industry. For instance, Verisk Analytics sets the de facto industry standard on language – “court-tested” and found in 200mn of the 250mn policies issued in the US – used in policy forms sold to insurers via subscription that ensures consumers are getting the same amount of coverage for the same quote across insurers.
The company sits at the center of a network that procures data from a wide variety of sources (claims settlements, remote imagery, auto OEMs), analyzes it, and delivers predictive insights to clients (insurers, advertisers, property managers). The agreements through which a customer licenses VRSK’s data also allows the company to make use of that customer’s data….so essentially the customer pays Verisk for a solution that costs almost nothing for the company to deliver and Verisk gets to use that customer’s data to enhance its own solutions, which improved solutions reduce churn and attract even more customers (and their data) in a subsidized feedback loop. This flywheel, built on top of Verisk’s historical advantage as the repository of industry data, has generated world’s largest claims database (VRSK aggregates claims data from 95% of the P&C industry), containing granular information on 1.1bn claims (up from 700mn claims in 2011), with the insurance ecosystem submitting ~200k new claims a day across all P&C coverage lines. It would be effectively impossible for a competitor to replicate this ever-burgeoning flurry of data.
[Aside: VRSK’s spending on public clouds has dramatically escalated over the last few years, allowing the company to not only realize considerable cost savings (without public clouds, it would have been far more costly for Verisk to secure engagements with European retail banks, who operate under strict privacy laws that require data to reside within the country of origin) and flexibility as its datasets continue to expand in girth and complexity, but to also apply machine learning to those datasets and enable new functionality to its services].
Comprehensive data paired with a decent model generates better insights than limited data paired with a great model. An insurer that relies solely on in-house claims experience cannot underwrite risks with nearly the same degree of accuracy as one with access to the entire industry’s data. Consider all the vehicle ratings variables – make & model, location where the car is garaged (down to one of 220k census blocks), mileage, driver’s record, semi-autonomous / safety features in the vehicle – that VRSK accounts for in assessing loss costs on 323 ISO series cars (cars that are part of the ISO ratings series used to match premiums to type of car). Or the construction costs – from roofing material to drywall to electrical and HVAC contractor rates – monitored across 460 regions across North America and updated monthly using Verisk’s Xactimate software, which insurers use to quantify replacement costs, including labor and material costs, within 21k unit-cost line items in the event of a claim and compare computed insurance-to-value estimates to those submitted by brokers at the beginning of the underwriting process. A contractor who shows up to a damaged home after a storm can leverage the 100mn price points stored in Verisk’s database, estimate a policy claim, and then share that information with the policyholder, adjuster, and the claims department. Like Verisk’s policy forms, Xactimate, too, is an industry standard used to estimate nearly 90% of all personal property claims in the US.
Data is further leveraged to improve efficiency and the front-end experience of insureds. For instance, per one case study, a large auto insurer typically spent 15 minutes walking a policy seeker through its sales funnel (an initial 40-question quote inquiry that transitioned to processing, where 35% of qualified leads had their initial quotes changed, and finally to binding), with lead leakage at each step along the way, ultimately translating into a conversion rate of just ~7%. With Verisk’s LightSpeed, the insurer spent less than a minute on the sales process and doubled its conversions. By sifting through a deluge of 300mn transactions per month pulled from odometer readings, vehicle reports, and claims loss history, Verisk only needs a few pieces of information from the customer upfront to arrive at the right price within seconds at the point of quote.
With claims settlements absorbing 2/3 of the $600bn of premiums collected by the US P&C industry every year (not to mention the $6bn-$8bn of fraudulent auto injury claims), and the industry as a whole generating negligible underwriting margins over time, solutions that improve operating efficiency, improve sales outcomes, and accurately estimate the industry’s largest expense item, are obviously critical. Verisk’s products are tightly integrated into customers’ workflows and consumed as subscriptions (subscriptions represent ~85% of the company’s revenue).
1) Is the transformed data proprietary? Check
2) Are the insights from the data critical? Check
3) Does the data fuel a feedback loop that deepens the data moat? Check.
VRSK has a nice moat in the P&C vertical. But of course the best companies not only have dominant competitive advantages around their existing business, but also huge advantaged growth opportunities, and it is here, I’m afraid, that prospects look bleaker. Here are what management sees as its growth opportunities:
Selling existing products to new customers and introducing new products to existing ones. This is the most compelling opportunity from a probability-of-success standpoint and has motivated much of the recurring tuck-in acquisitions made by the company over the years. Over the last several years, the company has re-oriented how it approaches the customer, moving away from a siloe’d approach to product sales to integrated teams: most of the company’s sales to insurers are bundled products that improve customer stickiness