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Reports Show That A.I. Bias Caused 80% Of Black Mortgage Applicants To Be Denied

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Reports Show That AI Bias Caused 80 Percent Of Black Mortgage Applicants To Be Denied

Artificial intelligence, with its inherent bias, appears to be a persistent element in the stalling of minority home loan applications. Lenders were more likely to deny house loans to persons of color than to white people with the same financial qualities, according to a study by The Markup. Specifically, 80 percent of Black candidates, as well as 40 percent of Latino applicants and 70 percent of Native American applications, are more likely to be rejected. How dangerous is the hidden bias in mortgage algorithms?

What You Need to Know About the Breakdown:

According to CultureBanx, 45 percent of the country’s leading mortgage lenders already provide online or app-based loan origination, indicating that FinTech is poised to play a significant role in decreasing bias in the home lending industry. Not to mention the fact that under algorithmic lending, minority borrowers who are approved online generally pay more. Minority families accounted for $2.25 trillion of the $13 trillion in outstanding household debt in the United States in 2017.

The Associated Press dug deeper into this issue by city using an examination of 17 key constant characteristics from over two million conventional national mortgage applications. It was discovered that lenders in Chicago were 150 percent more likely to reject Black applications than white ones. In Waco, TX, the situation is much worse, with lenders rejecting Latino applications at a rate of more than 200 percent higher than white applicants.

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The High Stakes of Homeownership:

The major cause of the racial wealth gap is disparities in homeownership rates. According to various studies, the average white family has more than ten times the average African American family’s wealth. According to McKinsey, bridging the racial wealth gap could benefit the US economy between $1.1 trillion and $1.5 trillion by 2028, with homeownership playing a key role.

When it comes to house loans, AI-based lending should be much more altruistic because they don’t want to leave any money on the table. “If lenders discriminate in the accept/reject decision, money is left on the table,” according to research by the National Bureau of Economic Research. “Such unprofitable discrimination must reflect a human bias by loan employees.”

According to the US Census Bureau, Black homeownership has slipped to its lowest level, at 40%, and has been continuously dropping since its high in 2004. Researchers estimate that between 2009 and 2015, 0.74 to 1.3 million minority applicants were refused, despite the fact that they would have been accepted if loan officers had not discriminated against them.

What Then Is Next

While loan officers at each institution make formal lending choices, they are mostly guided by software, the majority of which is regulated by a pair of quasi-governmental bodies. The analysis of The Markup was criticized by the American Bankers Association, the Mortgage Bankers Association, the Community Home Lenders Association, and the Credit Union National Association. The devil is in the algorithmic details and actual homeownership numbers, which have been steadily declining for African Americans in recent decades.

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