Consumer Watchdog opposes proposal for black-box models in wildfire risk prediction

Consumer Watchdog opposes Californian Insurance Commissioner Ricardo Lara’s proposal to allow insurance companies to use black-box catastrophe models and artificial intelligence (AI) for predicting catastrophic wildfire risks, citing concerns that this approach will increase home insurance rates without transparency or accountability.

These concerns were voiced during Consumer Watchdog’s testimony at the Department of Insurance “Catastrophe Modelling and Ratemaking” Workshop on Tuesday, April 23rd.

Consumer Watchdog highlights the proposal’s failure to ensure the accuracy and fairness of private models through testing, the absence of uniform standards for their use, and the lack of requirement for insurers to gain approval for a model’s reliability before implementing rate hikes.

Additionally, the proposal mandates secrecy by compelling any party seeking information about a model’s impact on insurance prices to sign a nondisclosure agreement.

Furthermore, Consumer Watchdog urges California to develop a public model that would be fully open to public scrutiny, arguing that the current approach violates California law passed by voters in Proposition 103, which mandates insurance companies to disclose all factors affecting insurance prices.

Carmen Balber, executive director of Consumer Watchdog, stresses, “Mandating non-disclosure agreements to meet the confidentiality demands of private black box modellers will prevent regulators and independent public interest groups from testing models’ accuracy and from sharing their analysis with the public.”

“Catastrophe models will simply be tools for insurance companies to charge more unless Commissioner Lara agrees to public scrutiny into how models impact prices, requires review and approval of their design and use, and requires that insurance companies use them to provide consumers and communities with actionable information about how to reduce their premiums by reducing their own climate risk,” Balber adds.

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