Artificial Intelligence and its inherent bias seems to be an ongoing contributing factor in slowing minorities home loan approvals. An investigation by The Markup found lenders were more likely to deny home loans to people of color than to white people with similar financial characteristics. Specifically, 80% of Black applicants are more likely to be rejected, along with 40% of Latino applicants, and 70% of Native American applicants are likely to be denied. How detrimental is the secret bias hidden in mortgage algorithms?
The Breakdown You Need to Know:
It’s important to note that 45% of the country’s largest mortgage lenders now offer online or app-based loan origination, as FinTech looks to play a major role in reducing bias in the home lending market, CultureBanx reported. Not to mention that with AI involved minority borrowers who get approved online, they’re typically paying more under algorithmic lending. In 2017, $2.25 trillion of the $13 trillion of outstanding household debt in the U.S. was associated with minority households.
Through an analysis of 17 different constant factors of more than two million conventional national mortgage applications, the Associated Press looked deeper into this matter by city. It found that Chicago lenders were 150% more likely to reject Black applicants than similar white applicants. In Waco, TX , the situation is even worse because lenders were more than 200% more likely to reject Latino applicants than white applicants.