Available here. Here are a few of the key findings of the study which examined the use of credit-based scores to determine automobile insurance rates:
- Scores effectively predict the number of claims consumers file and the total cost of those claims. Their use is likely to make the price of insurance better match the risk of loss that consumers pose. Thus, on average, as a result of the use of scores, higher-risk consumers pay higher premiums and lower-risk consumers pay lower premiums.
- Use of scores may result in benefits for consumers. For example, scores permit insurers to evaluate risk with greater accuracy, which may make them more willing to offer insurance to higher-risk consumers for whom they otherwise would not be able to determine an appropriate premium. Scores also may allow insurers to grant and price coverage more efficiently, producing cost savings that could result in lower premiums. Little empirical data was submitted or available to the FTC that would allow the agency to quantify the magnitude of these benefits.
- Scores are distributed differently among racial and ethnic groups, and these differences are likely to have an effect on the premiums that these groups pay, on average.
- As a proxy for race and ethnicity in statistical models of insurance, scores have a 1.1 percent and 0.7 percent effect for African-Americans and Hispanics, respectively. This means that most of their predictive power is not as a substitute for membership in racial or ethnic groups. In addition, scores effectively predict risk of claims within racial and ethnic groups.
- The Commission could not develop an alternative scoring model that would continue to predict risk effectively, yet decrease the differences in scores among racial and ethnic groups. The results of these efforts indicate that there is no readily available alternative scoring model that would achieve those results.
UPDATE: Luke Froeb (Vanderbilt and former Director of the Bureau of Economics at the Federal Trade Commission) offers some thoughts on the FACTA study at his new blog: Management R&D:
So even though credit scores help insurance companies price insurance more accurately, point 3 implies that some groups pay more, on average, than others. The policy issue behind the study is whether the government ought to ban the use of credit history for anything but making loans. As point 4 implies, banning the use of credit scores would result in higher prices for good drivers, regardless of their race or ethnicity.
Theory tells us that in states which ban the use of credit scores to price insurance (California and Massassachusetts) insurance companies would find it more costly to distinguish high from low risks, so they may lump them together (called “pooling”), and price insurance at the average risk. Or they may be concerned that only high risks would be willing to buy high-priced insurance (what economists call “adverse selection”) and price high or, if price controls prevent high prices, exit the market.