Today, insurers can access more data than ever. Why is this a problem, and why is this an opportunity for Groundspeed?
Well, it is true there is more data than ever. That said, I believe we are probably in the very early innings of utilizing the new forms of data that are becoming available to genuinely improve risk selection and pricing. Nonetheless, information from IoT [internet of things] devices or high-def information about properties are examples of data that will be important over time. The truth of the matter is that in meaningful parts of the insurance marketplace—such as in the middle market, the complex commercial insurance segments, as well as the specialty insurance categories—very large and important swaths of data are still traded in a variety of formats and usually as unstructured electronic documents.
It is unlikely, given the complexity of that information, that the industry is going to come around to a set of standards soon. So technology has the potential to really bridge that gap in a much faster manner.
For brokers and carriers, what is the potential value that they’re not getting now from all that unstructured data, whether it’s paper, PDF or Excel spreadsheets?
On the broker side, there is foundational information that can be unlocked just from the existing book of business. Take for example, understanding the underwriting profitability that brokers are producing for their markets. Or understanding program structures for a specific segment or portfolio of business. Having ready access to this information to advise clients or create proprietary products would be invaluable. That information inevitably exists somewhere within the brokerage—the policy documents, loss runs, exposure schedules, quote responses. Similarly, for carriers, they’re seeing tens of thousands of submissions a year, and they may be quoting some portion and writing a fraction of what they quote. Yet vast information is lost through this process—it is available if it could be harvested. This flow offers tremendous opportunity to better understand the marketplace if carriers had a way to make sense of it and structure it in an efficient, cost-effective way. And that is part of problem that we see and that we’re trying to solve.
Besides providing a clearer picture of where the businesses and clients are now, can tools like artificial intelligence and data analytics also provide a more predictive outlook?
AI is at the core of everything we do, and we’re seeing exactly this sort of demand from our clients. Let me give you a simple example from a carrier perspective for commercial auto. If you’re a carrier, when you get loss information as part of the submission, that loss information does not necessarily make a clear determination about who is at fault for each claim. This information for many is critical in assessing and pricing risk. And there is an example where, if you had the predictive analytics to be able to make that kind of assessment, the risk selection and pricing could be that much more accurate.
We’re seeing lots of very specific demands like that, and we’re also seeing more general, broader interest from our customers, such as: “Could you give us a view on whether this is a higher or lower risk within a comparable cohort, and why do you see that as being a higher or lower risk?” Frequently that kind of insight is something that provides a perspective on a risk that might be different than some of the key features that carriers use to select or rate the client. That’s the kind of insight that I believe we can provide with predictive analytics over time.
You come from a venture capital background. When you’re looking for investment and thinking about insurtechs, what do you look for?
When I came into venture capital, I looked at it through the lens of very much an enablement of the industry. You know, I’m not a big believer in the disruptive thesis. I think that great companies are leaders for a reason and they are competent and capable to leverage new technologies. So a core investment thesis was really about enterprise solutions and the way to make really great carriers and great brokers even better. That drove the investment thesis for the work that we were doing at Oak HC/FT, my former company. I’m still there as an advisor, and the incumbent enablement continues to be the thesis today.
We’ve made investments in companies like Clara Analytics that are using artificial intelligence to improve the outcomes of losses and reduce the loss adjustment expense. And I think you’ll continue to see investments from Oak focused on improving the economics of the existing industry participants. Their investment in Groundspeed was very much in that vein. They see the potential for us to apply new technologies for the benefit of improving the performance, the economics and the competitiveness of the incumbent carriers or brokers.
What attracted you to Groundspeed specifically?
We’re a three-year-old company, and the CEO and founder, Jeff Mason, and I had a preexisting relationship because in my prior life I tried to acquire a company he had previously helped to start. It was an interesting MGA/risk retention group in the professional liability space. So I got to know him through that experience and maintained a relationship.
When he shared with me that he was going to create Groundspeed, we stayed in touch. When it came time to raise the Series A, I provided him a lot of help. That was an institutional round, but I invested myself and joined the board at the time. When it came time to raise a Series B, and I was with Oak HC/FT, Oak was very interested in making the investment, and part of the decision around that investment was my involvement in developing the business going forward.
I always knew I wanted to go back into an operating capacity, and I knew that I would want to focus on technology as the next step in my career. This just emerged as the right opportunity, and Groundspeed was really pleased to have Oak as a backer because you have a very well respected, very successful investor, and they put a very sizable chunk of money—a $30 million investment—into the company. This was the largest enterprise solution insurtech investment in the industry for all of 2018. I was very excited to be part of that investment and join to help drive the development of the business with Jeff.
Where is the business going?
Today, we have a core product that we’ve developed that supports a range of what we call use cases or scenarios that are very high value to our broker and carrier clients. We are working hard to perfect that, which basically means we’re doing intensive development of our technology platform so we can harvest information from loss runs, exposure schedules, policies, applications, quote response and other related documents regardless of how that data is presented. We provide back-structured information and predictive analytics from those source documents. That’s really our focus today.
Related to the question earlier about where AI is coming into play, our clients are asking us to apply our data science capabilities toward a range of predictive analytics that can be generated from the information we are harvesting in these documents. We see that as being kind of the next horizon. Fortunately, we already have several clients who are working with us in this capacity.