Why California's telematics bill leaves insurers guessing on AI

Will auto insurers be allowed to use AI to evaluate the telematics data that California legislation would allow them to collect to set rates? It depends who you ask. 

The author of the bill says the legislation wouldn't permit the use of AI, while a consumer advocacy group in the state says it could.

AB 311, the Consumer Driving Data Protection Act, first introduced in January and most recently amended by the State Senate on July 9, would allow auto insurers to use a scoring model, defined in the bill as "a computational, statistical, actuarial, or algorithmic methodology capable of evaluating telematics data, or the inferences derived from those methodologies, to generate a numerical score or predictive assessment used directly or indirectly in rating automobile insurance."

Terry Schanz, chief of staff for state assemblymember Tina McKinnor, the bill's author, said the omission of the term "AI" speaks for itself. 

"There is no AI usage in the legislation or in the application of the law," Schanz said. "The technology, which is already used in 49 other states, simply records a driver's actions and uses that data to determine a driver's insurance rate."

Schanz added that the bill requires insurers to get opt-in consent from drivers for collecting telematics data.

Consumer Watchdog

Carmen Balber, executive director of Los Angeles-based consumer advocacy non-profit Consumer Watchdog, said the scoring model, also known as predictive algorithmic modeling, could include the application of AI to produce predictions — in this case, auto insurance risks for setting premiums.

Collected telematics data could also be used to train scoring models or algorithms developed in the future, Consumer Watchdog warns in an article. "Once a large language model has been trained on data, deleting the data doesn't remove the data's influence on the LLM," writes the author, Justin Kloczko.

If AB 311 becomes law, the California Department of Insurance, the state's insurance regulator, would still have the authority to review how insurers apply predictive algorithms to auto insurance risks and rates, according to Katie Klutts Wysor, principal in the insurance practice at PwC.

AB 311 would allow insurers to segment auto policyholders based on telematics data showing their risks, Wysor added. If passed, the bill would improve the auto insurance market in the state, she explained.

"California is a very hard state to do business in for auto insurers. You can't really segment. Therefore, if you're not segmenting well on pricing, you're at risk of attracting business that you typically in any other state would charge more for — because of the risk profile, because the rate to risk is actually higher," she said. "But there's no way for you to get to that rate to risk in California. There's modeling techniques you're not allowed to use. The result is so few people are really good risks. The whole thing is flattened out because you can't get the right segmentation in the book."