US mortgage approval algorithm more likely to reject people of colour 

Occurred: August 2021

US mortgage lenders were much more likely to turn down Latino, Asian, Native American and Black applicants than White ones, according to an investigation. 

An assessment of mortgage data by The Markup, co-published by the AP, discovered that mortgage loan applicants of colour were 40-80 percent more likely to be denied than their White counterparts across the US, and that the disparity was greater than 250 percent in some urban areas.

The complex statistic analysis of more than two million conventional mortgage applications for home purchases found that lenders were 40 percent more likely to turn down Latino applicants for loans, 50 percent more likely to deny Asian/Pacific Islander applicants, and 70 percent more likely to deny Native American applicants than similar White applicants.

The investigation also found that lenders in 2019 were more likely to deny home loans to people of colour than to white people with similar financial characteristics.

The algorithms used by lenders were mostly mandated and mortgage applications approved by Freddie Mac and Fannie Mae, whose own automated underwriting algorithms are a closely held secret.

The findings suggested that there was a hidden bias in mortgage-approval algorithms, leading to significant racial disparities in loan approvals. 

February 2024. The Markup's investigation was cited by Senator Ron Wyden as a reason for the introduction of the US Algorithmic Accountability Act of 2022. 

Operator: Freddie Mac; Fannie Mae
Developer: Freddie Mac; Fannie Mae
Country: USA
Sector: Banking/financial services
Purpose: Assess mortgage applications
Technology: Underwriting algorithms
Issue: Bias/discrimination - race, ethnicity
Transparency: Governance; Black box

Page info
Type: Incident
Published: August 2021
Last updated: June 2024