The number of consumers eligible for an auto loan could jump 11 percent a year if lenders use trended data, according to Equifax’s December 2016 Consumer Credit Impact analysis.
Trended credit data provide up to two years of consumer payment patterns and history, including scheduled payments, actual payments and past balances.
Especially in the automotive industry, Equifax expects more reliance on data insights as the market settles into a “post-recession norm,” a company statement said. “It will be vital to leverage as many insights about consumer debt behavior as possible to more confidently assess risk for a stable portfolio performance in support of a healthy loan marketplace.”
Equifax began using trended data for mortgage underwriting in September. It’s currently testing a specially designed risk-assessment model for auto lending. The credit bureau took a 5 percent sample from its national credit file and analyzed trades. It compared the auto risk-assessment model without trended data and with trended data to conclude that auto loan accounts could rise 11 percent a year if trended data is used, Peter Maynard, senior vice president of global analytics at Equifax, told Automotive News.
For example, one customer might pay off his balance monthly or pay more than the minimum amount due. Another consumer might make only minimum payments, but make them on time every month. If their profiles are otherwise about the same, the consumer who pays off the balance monthly or pays more than the minimum amount due would be considered lower risk based on trended data, the statement said.
Using trended data illustrates the difference between a “snapshot and a motion picture,” Maynard said. “By using trended data you really do understand the consumer a lot better.”
If the lender is able to see that consumers pay ahead of schedule, “that’s really powerful” for assessing risk, Maynard said. It means they are more likely to pay ahead on the loan they are applying for.
In Equifax’s auto loan overpay analysis, it found that 77 percent of consumers who overpaid in year one also overpaid in year two. For those who overpaid in year one but did not in year two, “that nuance is very important,” Maynard said.
“Are they changing their overpayment behavior because of less income or availability of resources to pay? Did they just take out … or are they about to take out a new-car loan?” Maynard said. “We don’t know the answer, but it creates the question.”
With the data, lenders are better able to understand how consumers’ behavior changes over time and whether that change sustains, Maynard said.
“The world is now changing as it relates to data,” he said. “New data sources, new capabilities are continually emerging. It’s important for lenders to keep abreast of these changes to improve customer experiences,” he said.