Latest CFPB data shows wide racial disparity in loan approval rates by Navy Federal
WASHINGTON, D.C. – Consumer Reports is urging the Consumer Financial Protection Bureau today to examine whether Navy Federal Credit Union is engaged in discriminatory underwriting in light of a recent CNN report analyzing CFPB mortgage data that found that Black applicants were more than twice as likely to be denied as White applicants with the same financial profile. CR has launched a petition calling on the CFPB to investigate and provide more clear guidance to all lenders to ensure that the algorithms they use to evaluate borrowers don’t result in unfair discrimination.
According to the report, Navy Federal, the largest credit union in the country that lends to military service members and veterans, approved 75 percent of all mortgages to white borrowers, but less than 50 percent of all Black borrowers who applied for the same type of loan. This was the widest gap observed among the top 50 lenders who originated mortgages last year.
CNN reported that Navy Federal approved loans for Latino applicants at significantly lower rates than whites. The revelations about Navy Federal have prompted attorneys to file a class action lawsuit alleging that the credit union has discriminated against Black and Latino applicants.
“Black and Latino borrowers historically have faced discrimination accessing affordable mortgages that has prevented many families from realizing the dream of home ownership and building wealth,” said Jennifer Chien, senior policy counsel for financial fairness at Consumer Reports. “The large racial disparity found between loan approvals for applicants with roughly the same financial profile raises serious concerns that Navy Federal may be unfairly discriminating against Black and Latino applicants.”
Chien continued, “Navy Federal’s stark racial gap highlights the need for stronger and clearer regulatory guidance on the application of fair lending rules to automated underwriting models. The CFPB should provide more explicit guidance for lenders to ensure that computer algorithms used to assess creditworthiness don’t discriminate.”
Despite longstanding fair lending rules, the racial approval rate gap has increased in recent years and continues to represent a larger nationwide problem. Discrimination can arise from disparate treatment when lenders intentionally treat consumers differently based on protected characteristics. It can also arise from disparate impact, when underwriting models produce outcomes that systematically disadvantage certain groups.
The increasing use of automated underwriting systems by lenders such as Navy Federal has increased the risk of bias being embedded into such systems through the use of biased or unrepresentative data, proxy variables for protected characteristics, and disparate impact. The technology now exists for lenders to identify less discriminatory underwriting models that do not sacrifice accuracy and predictiveness, and lenders should be required to seek out these alternative models.