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A secret bias against Blacks exists in mortgage approval algorithms

By Anthony SanFilippo
November 2021

Systemic racism is defined as a form of racism that is embedded in the laws and regulations of a society or an organization.

Who knew that included mathematical algorithms?

An investigation done by The Markup, and first reported on by The Associated Press, found that algorithms lenders use to determine whether or not an applicant qualifies for a home mortgage have an inherent bias against minorities – mostly Black applicants – making their path to achieving homeownership and building wealth exponentially more difficult.

The investigation found that lenders gave fewer loans to Black applicants than white applicants, even when they both had high incomes – more than $100,000 a year – and 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,’” José Loya, assistant professor of urban planning at UCLA who has studied public mortgage data extensively and reviewed the methodology of the study, told the Associated Press. “(This) work shows that’s not true.”

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The Markup provided a case study – one that took place in Charlotte, N.C.

They told the story of Crystal Marie and Eskias McDaniels who wanted to move cross-country from Los Angeles to Charlotte.

They found the home they wanted – a four-bedroom, 2,700 square foot house close to a playground and public pool for their son, Nazret. The price was set at $375,000.

The couple had saved enough money for a down payment, had very good credit – Crystal’s score was 805 while Eskias’ score was 725 – and each made a six-figure salary. After doing the calculations, it was determined that their monthly mortgage would actually be less than what they had been paying in monthly rent in Los Angeles.

Closing was scheduled for a Friday in August 2019. They even booked their movers for the same day.

A mere 48 hours before they were going to close, Crystal Marie got a disheartening phone call from the loan officer – they weren’t going to qualify for the mortgage.

The officer told her that the application was submitted and re-submitted a total of 17 times and each time it came back as not approved. It cost Crystal and Eskias $6,000 in non-refundable fees.

The reason given that they were denied the mortgage was that she is considered a contractor at her job, and not a full-time employee, even though she was never at risk of losing her job. By comparison, all of her co-workers were also considered contractors. They all had mortgages.  Of course, her co-workers all are white. She and Eskias are Black.

Results of Investigation

The investigation found that in 2019, even when a control was in place to account for newly available financial factors that the mortgage industry insisted would eventually explain such lending disparities, that nationally, lenders were 40 percent more likely to turn down Latino applicants for loans, 50 percent more likely to turn down Asians or Pacific Islanders, 70 percent more likely to deny Native Americans, and a whopping 80 percent more likely to turn down Black Applicants.

The Markup used a digital embed, developed by Ben Tanen exclusively for this investigation, to determine how many people of each ethnicity would be denied a mortgage assuming 100 similarly qualified applicants applied. The only difference on paper was their race.

Critics of such an assessment had previously argued that there were missing ingredients to the data that led to such disparate outcomes – such as lending rates, or debt percentages compared to income, or even a property assessment value compared to the borrow ask.

However, thanks to the Home Mortgage Disclosure Act, most of these financial factors are now public and were included in this investigation.

The investigation, when shared with industry leaders, was widely criticized for info it didn’t include – such as credit scores, which aren’t publicly available, but not one critic could point to an inaccuracy in the data compiled.

Another critique was that The Markup only investigated conventional loans and didn’t include federally backed loans.

However, government loans bring people who otherwise wouldn’t qualify for loans into the market, and they tend to be more expensive, long-term, for the borrower.

The Markup defended that decision by pointing out that the Federal Reserve and Consumer Financial Protection Bureau, the agency that releases mortgage data, separate conventional and Federal Housing Administration (FHA) loans in their research on lending disparities. Authors of one academic study out of Northeastern and George Washington universities said they focus on conventional loans only because FHA loans have “long been implemented in a manner that promotes segregation.”

Disparities Differ Based on Location

In addition to finding disparities in loan denials nationally, the investigation focused on several cities and communities across America.

While Charlotte saw a disparity of about 50 percent when it came to loan approvals between whites and Blacks, it was hardly the most egregious location.

Chicago was 150 percent more likely to deny a loan application from Black people than white. Minneapolis was 100 percent more likely to deny a loan application from a Native American, while in Waco, Texas, lenders were 200 percent more likely to deny a Latino Application.

Of course, this all stems from the now illegal practice of redlining, which identified the boundaries of specific neighborhoods – predominantly Black or immigrant-filled – that were deemed too risky for financial investment.

That practice started in Chicago in the 1930s and was happening well into the 1970s, with its impacts still being felt today.

“When you see that maybe the tactics are different now, but the outcomes are substantially similar,” Chicago 47th Ward Alderman Matt Martin told the Associated Press. “It’s just not something we can continue to tolerate.”

While it is assumed that lending officers are making these approval or denial decisions, the reality is computer software mandated by Fannie Mae and Freddie Mac does most of the work.

Fannie and Freddie set the rules of the industry and they require lenders to use a specific credit scoring algorithm – the classic FICO score – to determine if an applicant reaches the minimum credit threshold for approval. That score is currently 620.

However, that algorithm was created in 2005 and it used data from the 1990s, which automatically puts people of color at a disadvantage because it rewards traditional credit, which white Americans have always had more access to. It doesn’t consider on-time payments of other living essentials like utility bills, or rent, or cell phone bills – but it will punish them for late payments if they are sent to debt collectors. It also penalizes people for past medical debt – even if it’s been paid.

Newer Credit Model Addresses Flaws

It’s not like there aren’t fairer credit models. One developed by the big three credit bureaus – Equifax, Experian and TransUnion – believes it would grant credit to 37 million Americans that currently have no FICO score.

But for reasons unexplained, Fannie and Freddie have stuck with their outdated model despite many calls for them to change – including from the company that originally created FICO.

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


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