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Insurance sector set for digital revolution: Lemonade CEO

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LAS VEGAS — Insurtech companies have already changed the way some insurance products are sold, but “you ain’t seen nothing yet,” said Daniel Schreiber, CEO of Lemonade Insurance Co.

Start-up insurers using digital technology and artificial intelligence are gathering vast amounts of data that will revolutionize the way risks are assessed and priced, he said at the InsureTech Connect conference Wednesday in Las Vegas.

As a result, in 10 years, the insurance buying process will be very different than it is today, Mr. Schreiber said.

“The next insurance leaders will use bots not brokers and AI not actuaries,” he said.

Insurance industry incumbents have in many cases dominated the sector for centuries, but they will have a much harder time going forward, said Mr. Schreiber.

Lemonade, which was established two years ago, offers renters insurance and has a highly digitized underwriting and claims system.

Numerous insurtech companies are already established, but “everything that we’ve seen so far is just the tip of the iceberg,” Mr. Schreiber said.

Using digital technology, insurtech companies can establish operations in the market and incur far lower costs, he said. For example, Lemonade, which has about 250,000 customers and fewer than 100 employees and uses bots to sell coverage, pay many of its claims and manages its back office, Mr. Schreiber said.

“When you use technology well, you don’t just collapse costs, you delight consumers, because computers will operate in a faster way and give instantaneous responses,” he said.

Going forward, technology will transform insurance even more radically, Mr. Schreiber said.

Insurance is essentially an algorithm, he said. “Insurance is about using statistics to price risk, which is why data, properly collected and used, can transform the core of the product,” he said.

With greater availability of data, obtained through digital interactions with customers, insurers can gather huge amounts of information that is highly predictive and are able to differentiate more accurately between policyholders and price risks more precisely, Mr. Schreiber said.