Data Mined Auto Loans
Americans need their automobiles.
According to the Annie E. Casey Foundation, 88% of Americans drive to work and two-thirds of new jobs are located in suburban areas away from public transportation systems. Relying on public transportation, if available, can drastically increase commute time and take time away from important life activities. Without a car, a person’s options for work, childcare, education, and shopping for households necessities become extremely limited.
Improve economic access in your community.
Credit unions in the pilot have agreed to offer the program, which employs sophisticated data mining techniques to identify households that may benefit from an affordable auto loan. Based on underwriting criteria, members would qualify for an auto loan at either traditional or non-prime rates. Data mining has proven successful with traditional and non-prime lending and here we will test the same approach for minority members who either have a high-rate auto loan or no auto loan at all.
250 credit unions have used similar techniques to write 300,000 loans worth $2.5 billion to members with credit scores under 640.
Previous iterations led to an average program ROA of 7.76%.
Fair Credit Reporting Act (FCRA) and Fair & Accurate Credit Transactions (FACT) Act compliant processes are incorporated.
Reach out to Adam Lee, incubator director, to learn more about this initiative.
Data Mined Auto Loans is one of five programs being tested in the Reaching Minority Households Incubator. Our work to research and test solutions to improve access to financial services is made possible by Visa.