The relentless improvement in personal lines pricing precision is eliminating the cross-subsidies that coarser rating systems created for decades -- and reshaping the market in ways that are positive overall but disruptive for specific segments.
Traditional personal lines rating used a relatively small number of variables: territory, vehicle type, driver age and history, credit-based insurance scores. Each variable was a proxy for risk factors that could not be measured directly. As telematics, alternative data, and machine learning enable more direct risk measurement, the proxies become less necessary -- and their imprecision becomes a competitive liability.
The beneficiaries of better pricing precision are low-risk insureds who were previously pooled with higher-risk peers in the same rating territory or demographic bucket. They receive more accurate (lower) prices. The segment receiving higher prices from more precise rating sometimes perceives this as discriminatory, even when it reflects actuarially justified risk differences.
The regulatory and public affairs challenge for the industry is communicating the distinction between actuarially justified risk differentiation and impermissible discrimination -- a distinction that requires both technical rigor and effective public communication.
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