Now Required in Auto Finance: Subprime Data & Analytics Expertise
As we look ahead to AFSA’s Vehicle Finance Conference, we want to examine key trends impacting automotive finance:
- Auto sales are declining towards recession levels. According to FRED, while vehicle retail sales recovered in the few years following the 2008 recession, 2014 marked the beginning of a new decline. Consumers are replacing their cars less frequently and new platforms like Uber are making it easier to not own a car altogether.
- Subprime customers are comprising more of the auto loan portfolio. According to McKinsey, subprime loans are nearing half of all auto loans. Given that auto sales are declining, this trend makes sense: auto lenders must lend to more subprime customers in order to maintain originations.
- Auto loan delinquencies are rising to record highs. According to the Federal Reserve Bank of New York, nearly 5% of the total outstanding balance was over 90 days delinquent in Q1 of 2019. While no single reason fully explains the rising delinquencies, the growth in subprime loans seems to be a key contributor. Another driver which is a growing challenge for many industries is synthetic identity fraud.
While the automotive finance industry is facing several obstacles, these obstacles are paving way for new opportunities. Enova International was one of the first online, state-licensed consumer lenders in the market. Operating under the belief that there is a way to profitably meet the credit needs of nonprime consumers, Enova has grown to a billion-dollar business.
What has made Enova successful is its discipline in using data and analytics to drive business decisions and innovation in technology to execute those decisions in real-time. Because nonprime consumers typically have thin credit profiles, Enova could not rely on traditional credit scores alone. As a result, Enova developed its own know-how in combining first-party and third-party data to predict behaviors such as fraud and willingness to repay to produce a credit decision within seconds of a customer submitting an online application.
“One of the largest breakthroughs we’ve had in fraud detection came out of a decision we made about nine years ago to analyze customer behavior on our website,” says Mike Failor, Senior Director of Risk Analytics at Enova International. “By identifying deviations from what is expected, we’ve been successful at preventing millions of dollars worth of fraud losses each year. And as we’ve implemented machine learning techniques, our fraud detection has become more robust over time.”
Enova Decisions has taken Enova International’s expertise in non-prime lending and decisioning technology and packaged them into an underwriting solution to help both captive and indirect auto lenders manage portfolio risk. Contact us today to learn how.