Artificial intelligence and its inherent bias appear to be a persistent factor slowing down minority housing loan approval. An investigation by The Markup found that lenders were more likely to refuse home loans to people of color than to whites with similar financial characteristics. Specifically, 80% of black candidates are more likely to be rejected, along with 40% of Hispanic applicants and 70% of Native American applicants are likely to be rejected. How detrimental is the hidden bias hidden in mortgage lending algorithms?
What you need to know:
It’s important to note that 45% of the nation’s largest mortgage lenders now offer online or app-based lending as FinTech hopes to play an important role in reducing bias in the home lending market. Culture reported. Not to mention, with AI, minority borrowers who get approved online tend to pay more with algorithmic lending. In 2017 $ 2.25 trillion out of $ 13 trillion in household debt outstanding in the United States has been associated with minority households.
The Associated Press analyzed 17 different standing factors in over two million common national mortgage applications. It found that lenders in Chicago were 150% more likely to reject black candidates than their whites. In Waco, Texas, the situation is even worse because lenders were more than 200% more likely to reject Hispanic candidates than whites.
High home ownership rates:
Inequality in the share of homeowners is considered to be the main cause of the racial wealth gap. There are several studies that show that the average white family owns more than ten times the wealth of the average African American family. McKinsey predicts that narrowing the racial wealth gap could improve the US economy. $ 1.1 trillion to $ 1.5 trillion by 2028and home ownership is an important component of this.
AI lending needs to be much more altruistic when it comes to home loans, due to the simple fact that they don’t want to leave money behind. A study by the National Bureau of Economic Research notes that “if lenders discriminate when making / rejecting a decision, it will mean that money will remain on the table. … (s) such disadvantageous discrimination must reflect human bias on the part of loan officers. “
The US Census Bureau reported that black home ownership has fallen to its lowest level of 40%, and has been steadily declining since its 2004 peak. It is possible that AI could help reverse this trend, as the researchers estimate that between 2009 and 2015, between 0.74 and 1.3 million minority applicants were rejected, who would have been accepted if it had not been for discrimination by credit specialists.
While home loan decisions are formally made by loan officers at each institution, they are mostly made by software, much of which is sanctioned by a couple of quasi-government agencies. The American Bankers Association, the Mortgage Bankers Association, the Community Housing Lenders Association, and the National Credit Unions Association criticized The Markup’s analysis. The real devil is in the algorithmic details and actual home ownership rates, which we know have continued to decline for African Americans over the past few decades.