In 2021, U.S. Chamber of Commerce’s Center for Capital Markets Competitiveness (CCMC) released the Economic Benefits of Risk-Based Pricing for Historically Underserved Consumers in the United States, which focuses on how risk-based pricing allows financial institutions, including insurers, to use analytics to better assess risks to offer innovative products at lower prices for consumers. Insurers provide financial protection against an individual’s future unknown costs related to insurable losses on products like homeowners and automobile insurance.
WHAT IS RISK-BASED PRICING AND HOW IS IT USED BY INSURERS?
Risk-based pricing allows lenders and insurers to offer different rates or other terms to consumers based on their individual risk
In general, insurers commonly use factors such as credit-based insurance scores (CBIS), location, driving experience, education, occupation, and property value into their risk models to predict the probability of nonpayment or insurance losses.
Importantly, variables like CBIS, education, and occupation that, on the surface, seem unrelated to auto or homeowners insurance have been shown to strongly predict the likelihood of losses for individuals and are valid components of risk-based pricing. CBIS models utilize credit history data but include only factors shown to statistically correlate with claim costs.
From an actuarial perspective, these factors are proven to predict risk and can improve the accuracy of risk-based pricing models so that insurers can better predict losses and offer consumers more competitively tailored rates.
HOW DOES RISK-BASED PRICING BENEFIT CONSUMERS?
Under a risk-based pricing system, costs are lowered for the majority of consumers who are deemed low-risk, while opportunities are expanded for higher-risk consumers.
The more accurately these models can predict risk, the more companies can offer lower rates and expand access to insurance, especially for underserved populations.
WHAT HAPPENS IF INSURERS ARE PROHIBITED FROM USING CERTAIN DATA?
Limiting or prohibiting the use of relevant data in risk-based pricing has negative consequences; firms must rely on less information to predict risk, which reduces accuracy and, ultimately, increases costs and decreases access to competitive credit and insurance products for consumers.
According to a 2020 study, “When insurers are prohibited from using an accurate rating variable, or the use of a variable is tempered, the average price for higher-risk policyholders decreases, and that of lower-risk policyholders increases.”1