What insurers really want out of AI

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The key to artificial intelligence startups' success in insurance is proving they can fix carriers underwriting and policy distribution woes, according to Carol Zacharias, QBE North America’s SVP of underwriting counsel for specialty insurance.

“Solve their problems, even if it isn’t your end game, and [carriers] will use your tech,” she said, during a panel discussion at the Exponential Finance conference in New York.

While AI adoption in insurance began at the front-end — through gathering connected-car data for risk mitigation, and bots for direct-to-consumer distribution — insurers are now targeting the back end, Zacharias adds. Achieving robo-underwriting, however, will be determined by how quickly carriers collect unstructured data and mine it, panelists said.

“The data is everywhere,” said Chris Cheatham, CEO & founder of insurtech RiskGenius, which applies AI algorithms to insurance contracts for the better understanding of policy language.

Compounding the problem is the complexity of the insurance industry, Zacharias notes. Complete AI adoption in insurance is inevitable, but it cannot be rushed. Startups should not walk into presentations offering up one overarching solution.

“You can’t do one size fits all,” said Zacharias. “AI for a health insurer is different than a 100-year-old national company. Same goes for one with a presence in 47 countries.”

Anatola He, director of product strategy at HyperScience joined Zacharias and Cheatham on the panel. Nigel Walsh, partner in Deloitte’s financial services technology practice served as the moderator.

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Artificial intelligence Insurtech Digital distribution QBE North America RiskGenius
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