In a study conducted by the Florida Atlantic University’s College of Business, African-American mortgage borrowers were more likely to receive higher interest rates than their white, non-Hispanic counterparts. The study, based on data available from the U.S. Survey of Consumer Finances, controlled for various factors available in the data, such as income, education level and shopping behavior. The results of the study yielded correlations that caught the attention of researchers (Source: National Mortgage Professional Magazine, 8/25/2015):

Dr. Cheng and his fellow researchers, Drs. Zhenghou Lin and Yingchun Liu of California State University, Fullerton, found that the rate disparity mainly occurs to young African-American borrowers with low education, as well as those borrowers whose income and credit disqualify them for prime lending rates. Additionally, among borrowers in the higher rate groups, African-American women seem to receive much more disparate treatment than African-American men.

“Our finding is that there is a discrepancy between blacks and whites in terms of mortgage rates,” Dr. Cheng said. “When we further dig into the data, we find that generally the low-income African-American women who are heads of households pay the highest. They are the most vulnerable to sub-prime lending and higher mortgage rates.”

The study does not control for loan, borrower and market characteristics that we normally consider in conducting a Fair Lending analysis, such as credit score, DTI, LTV and seller paid fees. Without these and dozens of other important factors, the results show correlation with demographic and behavior characteristics, not causation. However, the consideration of education level, shopping behavior and other characteristics that are not available in data collected by loan operating systems may yield useful insights for lenders to develop strategies that target groups presenting risk based on a thorough Fair Lending analysis. A lender that finds similar patterns of African-American women showing the greatest risk may leverage this information when crafting tactics that target the group’s unique socioeconomic and behavioral characteristics to improve Fair Lending performance.