In comments submitted by the Americans for Financial Reform Education Fund, Consumer Action, Consumer Federation of America, Consumers for Auto Reliability and Safety, Center for Responsible Lending, National Association of Consumer Advocates, National Consumer Law Center, on behalf of our low-income clients, UnidosUS and U.S. PIRG, we applaud the Consumer Financial Protection Bureau (“CFPB” or “Bureau”) for its efforts to enhance public data on auto lending and appreciate the opportunity to comment on the issue.
Auto credit and cars in general have an enormous impact on the majority of households, and auto credit is the third largest consumer credit market in the United States. Yet publicly available data is minimal and often excludes important portions of the marketplace and important details of the transactions—details that impact performance of the credit and success for consumers. The data is also highly aggregated, making it almost impossible to evaluate in a meaningful way. The opaqueness and asymmetry of information regarding data in the auto finance marketplace in many ways mirror the opaqueness and asymmetry of information between consumers and finance personnel in the finance and insurance “F&I” office at a dealership.
A data set built by the CFPB can and should address many of the current deficiencies in our knowledge of the auto finance marketplace through better and more available auto credit data. In order to create a robust data set that allows for better understanding of the market and its trends the CFPB should:
- Collect data from a broad variety of sources that reflects the broad array of credit transactions and creditors, and which focuses on the consumer experience rather than dollar volumes.
- Ensure that auto lending data is publicly available and usable, as granular as possible, and updated on a regular basis.
- Collect transaction level data about origination, consumer payment performance, and the entire repossession process from beginning to end.
- Collect data about consumer demographics, including race, ethnicity, age, gender, and other characteristics.
- Collect data about Buy-Here-Pay-Here finance entities, and subprime and regional financing entities.
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