Insurtech startups made lofty promises on disrupting incumbents. But they couldn’t leverage data as freely as they’d hoped—and struggled against ‘900-pound gorillas’ in the industry
By Isabelle Bousquette of The WSJ.
This reminds me of what economists call "asymmetric information." This
is a situation in which the seller knows more about a product than the
buyer (sometimes the buyer knows more about something important like how
healthy or risky they are as it relates to insurance). These markets do
not operate optimally. If insurance companies don't know how healthy or
risky you are, they can't be sure of how much your premiums should be. The idea here was that if insurance companies could use technology to track your driving habits, they could learn how risky you are and charge you the right premium. But it has not worked out that way. In some cases, state regulations have prevented companies from using the data they collected to set prices.
Excerpts:
"So far, the insurtechs have been slow to gather and contextualize enough data to actually build better models. Regulations have restricted the use of some of their data and differentiated pricing. And it has been difficult to chip away market share from established industry giants."
"But as far as transforming the risk analysis and pricing of insurance, that remains to be seen.
“To date, we’ve not really seen disruption,” said Jefferies analyst Yaron Kinar.
Data Problems
“We did a fairly shoddy job of pricing and identifying risks. And we knew we would,” said Lemonade co-CEO and co-founder Daniel Schreiber of the early days of the company. The problem was that Lemonade, along with other insurtechs, started without access to the historical data sets that incumbents have been gathering, in some cases, over many decades.
To build those more nuanced and complex sets of data takes time, Schreiber said. It isn’t just a matter of collecting enough data points, but also of identifying those that signify risk, which only happens once a claim is filed, he added.
It’s a similar story at auto insurance startup Root, which built its business around the use of telematics. Through a smartphone app, Root could track the driving styles of users for two weeks, then offer them a personalized price based on how they drove. But Root didn’t know for sure whether certain driver behaviors actually correlated to higher risk until accidents occurred and the claims started coming in, said Chief Executive and Co-founder Alex Timm.
Root grew fast, and in its early years had tens of thousands of claims coming in to work with. Once it was able to refine its model, the company went back and adjusted prices, Timm said.
But that was a risky play, said Jefferies analyst Kinar. The type of clients who gravitated to insurtechs were younger and more price-sensitive—meaning they were more likely to leave the platform if they saw a meaningful rate increase."
"Although startups had the digital-forward advantage of being able to collect tons more data points from smartphones, online interactions and other sources, regulations prevented them from actually using much of it for risk analysis and pricing."
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