HomeStructural racial bias in U.S. mortgage-approval, redlining: hidden software...

Structural racial bias in U.S. mortgage-approval, redlining: hidden software algorithms provide helping enforcement

Black applicants in Chicago were 150% more likely to be denied by financial institutions than similar white applicants there

Black applicants in Chicago were 150% more likely to be denied by financial institutions than similar white applicants there. Financial institutions were more than 200% more likely to reject Latino applicants than white applicants in Waco, Texas, and to reject Asian and Pacific Islander applicants than white ones in Port St. Lucie, Florida. And Native American applicants in Minneapolis were 100% more likely to be denied by financial institutions than similar white applicants there.

The new four-bedroom house in Charlotte, North Carolina, was Crystal Marie and Eskias McDaniels’ personal American dream, the reason they had moved to this Southern town from pricey Los Angeles a few years ago.

A lush, long lawn, 2,700 square feet of living space, a neighborhood pool and playground for their son, Nazret. All for $375,000.

Prequalifying for the mortgage was a breeze. They said they had saved much more than they would need for the down payment, had very good credit — scores of 805 and 725 — and earned roughly six figures each, she in marketing at a utility company and Eskias representing a pharmaceutical company. The monthly mortgage payment was less than they’d paid for rent in Los Angeles for years.

They were scheduled to sign the mortgage documents on Aug. 23, 2019 — a Friday — and were so excited to move in they booked movers for the same day.

The Wednesday before the big day, the loan officer called Crystal Marie, and everything changed, she said: The deal wasn’t going to close.

The loan officer told the couple he had submitted the application internally to the underwriting department for approval a dozen, 15, maybe 17 times, getting a “no” each time. The couple had spent $6,000 in fees and deposits — all nonrefundable.

“It seemed like it was getting rejected by an algorithm,” she said, “and then there was a person who could step in and decide to override that or not.”

She was told she didn’t qualify because she was a contractor, not a full-time employee — even though her boss told the lender she was not at risk of losing her job. Her co-workers were contractors, too, and they had mortgages.

Crystal Marie’s co-workers are white. She and Eskias are Black.

“I think it would be really naive for someone like myself to not consider that race played a role in the process,” she said.

An investigation by The Markup has found that financial institutions in 2019 were more likely to deny home loans to people of color than to white people with similar financial characteristics.

We found that financial institutions gave fewer loans to Black applicants than white applicants even when their incomes were high — $100,000 a year or more — and had the same debt ratios. In fact, high-earning Black applicants with less debt were rejected more often than high-earning white applicants who have more debt.

“Lenders used to tell us, ‘It’s because you don’t have the lending profiles; the ethno-racial differences would go away if you had them,’” said José Loya, assistant professor of urban planning at UCLA who has studied public mortgage data extensively and reviewed our methodology. “Your work shows that’s not true.”

“Redlining,” the now-outlawed practice of branding certain Black and immigrant neighborhoods too risky for financial investments that began in the 1930s, can be traced back to Chicago.  Chicago activists that banks were still redlining in the 1970s, leading to the establishment of the Home Mortgage Disclosure Act, the law mandating the collection of data used for this story.

Who makes these loan decisions? Officially, lending officers at each institution. In reality, software, most of it mandated by a pair of quasi-governmental agencies.

Fannie and Freddie, founded by the federal government, require lenders to use a particular credit scoring algorithm, “Classic FICO,” to determine whether an applicant meets the minimum threshold necessary to even be considered for a conventional mortgage, currently a score of 620.

This algorithm was developed from data from the 1990s and is more than 15 years old. It’s widely considered detrimental to people of color because it rewards traditional credit, to which white Americans have more access. It does not consider, among other things, on-time payments for rent, utilities, and cellphone bills — but will lower people’s scores if they get behind on them and are sent to debt collectors. Unlike more recent models, it penalizes people for past medical debt even if it’s since been paid.

“This is how structural racism works,” said Chi Chi Wu, a staff attorney at the National Consumer Law Center. “This is how racism gets embedded into institutions and policies and practices with absolutely no animus at all.”

Is America’s “White Cloud” receding?

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