What do you believe is the single most important factor driving up the cost of living in Nigeria?

Putting AI to use in mortgage lending decisions could lead to discrimination against Black applicants, according to new research. But researchers say there may be a surprisingly simple solution to mitigate this potential bias.

In an experiment using leading commercial large language models (LLMs) to evaluate loan application data, Lehigh researchers found that LLMs consistently recommended denying more loans and charging higher interest rates to Black applicants compared to otherwise identical white applicants.

This discovery is particularly alarming given the historical and ongoing racial disparities in homeownership.

"This finding suggests that LLMs are learning from the data they are trained on, which includes a history of racial disparities in mortgage lending, and potentially incorporating triggers for racial bias from other contexts," said Donald Bowen III, assistant professor of finance in the College of Business and one of the authors of the study, available as a working paper on SSRN.

The study used real mortgage application data, drawn from a sample of 1,000 loan applications included in the 2022 Home Mortgage Disclosure Act (HMDA) dataset, to create 6,000 experimental loan applications. In the experiment, researchers manipulated race and credit score variables to determine their effects.

• Read More