Nine large auto lenders were issued orders Thursday to provide information about their auto lending portfolios as part of a pilot program for collecting auto lending data, the Consumer Financial Protection Bureau (CFPB) said.
Announcing the orders, the CFPB said the nine lenders (which it did not name) represent a cross-section of the auto finance market. “The data collected from their responses to these orders will help us build a quality data set that provides insights into lending channels, loan performance, and inform potential future data collection efforts,” it said.
The pilot is described as a market-monitoring activity as provided in section 1022 of the Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank). A sample order included with Thursday’s release states that the information provided by the lenders “is intended to be used for monitoring for risks to consumers in the offering or provision of consumer financial products or services, including developments in markets for such products or services.” However, it also notes that the bureau “reserves the right to use and share internally the information for any purpose permitted by law.”
The bureau noted that it announced its intention to build a new auto lending data set last November, held discussions with stakeholders, and gathered public input into the auto lending areas “most in need of greater transparency.” It said a December stakeholder event identified three areas where “additional data visibility” would be important: lending channel differences; data granularity, consistency, and quality; and loan performance trends. It described these as follows:
- Lending Channel Differences. Currently, data is generally not broken down by whether the consumer secures financing for the purchase of the vehicle directly with a lender (direct lending) or whether the dealer arranges financing for the purchaser (indirect lending). As a result, it can be difficult – and in some cases nearly impossible – to analyze differences between direct and indirect auto loans.
- Data Granularity, Consistency, and Quality. Complete and comprehensive auto lending analyses are nearly impossible because of variations within existing data, the lack of a centralized data source, and the cost and significant burden of combining data sets. For example:
- The variety of lender types in the auto finance market can lead to data gaps. For example, depository institutions are required to submit regular call reports about their activities, while non-depository institutions do not have that same requirement.
- The use of different definitions and terms in various data sources leads to data quality issues. For example, data providers may use different credit score cutoff points when defining credit score tiers (superprime, prime, subprime, etc.). When data sets use different thresholds and data buckets, analysis across data sets is difficult or impossible.
- While some stakeholders may have access to sufficient data, those data sources are often prohibitively expensive, proprietary, and/or only available to certain market participants. Some data sets, even when publicly available, are only useful to individual market participants or small segments of the industry.
- Loan Performance Trends. There’s a lack of reliable information on repossessions, including how many days past due a loan typically is before a vehicle is repossessed, how long the consumer has paid on the loan before a repossession, and post-repossession impacts for the borrower and lender. Stakeholders have pointed to a need for more consistent and granular data on delinquency and default trends, specifically the correlation between delinquency and geography, credit score, and income.
The bureau said it has “taken care to ensure that no directly identifiable information – like name, address, or social security number – is collected as part of this pilot,” the bureau said in an announcement Thursday.
“As we collect data for and conduct this pilot, we will continue to inform the public of our assessment of gaps in auto data, where this data provides new insight into the market, and the next steps in scoping and building an auto finance data set that will help us better understand market trends,” it said.
CFPB announcement: Our auto finance data pilot