The Secret Bias Lurking in Mortgage Approval Decisions


The Markup is a non-profit newsroom that studies how powerful institutions are using technology to change our society. This story was reported by The Markup, and the story and data was distributed by The Associated Press.

The new four-bedroom home in Charlotte, NC was Crystal Marie and Eskias McDaniels’ personal American dream, the reason they moved from beloved Los Angeles.

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

Pre-qualifying for the mortgage was a snap – they had high credit scores, earned around six figures each, and had more than they needed for the down payment.

But days before they were supposed to sign, in August 2019, the loan officer called Crystal Marie with bad news: the deal was not going to end.

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

She was told that she was not eligible because she was an entrepreneur, not a full-time employee, even though her colleagues were also entrepreneurs. And they had mortgages.

Crystal Marie’s colleagues are white. She and Eskias are black.

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

A survey by The Markup found that lenders in 2019 were more likely to turn down home loans to people of color than to white people with similar financial characteristics – even when we controlled for new financial factors available as the industry. Mortgage claims in the past would explain the racial disparities in lending.

Holding 17 different factors stable in a complex statistical analysis of over 2 million conventional mortgage home purchase applications reported to the government, we found that, compared to similar white applicants, the lenders were:

• 80% more likely to reject black applicants

• 70% more likely to refuse Native American applicants

• 50% more likely to refuse applicants from Asia / Pacific

• 40% more likely to reject Latino applicants

These are national tariffs.

When we looked at towns and villages individually, we found disparities in 90 subways covering all regions of the country. Lenders were 150% more likely to reject black applicants in Chicago than similar white applicants there. Lenders were over 200% more likely to reject Latino applicants than white applicants in Waco, Texas, and to reject Asian and Pacific Islander applicants than white applicants in Port St. Lucie, Florida.

“The lenders were telling us, ‘It’s because you don’t have the loan profiles; ethno-racial differences would disappear if you had them, “” said Jos Loya, assistant professor of urban planning at UCLA who has studied the public mortgage data and reviewed our methodology. “Your work shows that this is not true.”

The American Bankers Association, Mortgage Bankers Association, Community Home Lenders Association, and Credit Union National Association have all criticized the analysis.

In written statements, the ABA and MBA rejected our findings for not including credit scores or government loans, which are mortgages guaranteed by the Federal Housing Administration, the Department of Veterans Affairs and others. .

Government loans have different approval thresholds, which bring people into the market who would not otherwise qualify, but generally cost buyers more. Even the Federal Reserve and the Consumer Financial Protection Bureau, the agency that publishes data on mortgages, separate conventional and government loans in their research into credit disparities.

Crystal Marie McDaniels stands outside her home in Charlotte, North Carolina.
– Nell Redmond / Associated press

We were unable to include credit scores in our analysis because the CFPB removes them from the public version of the data, in part due to lobbying from the mortgage industry, citing borrower confidentiality.

While mortgage loan decisions are formally made by loan officers, they are largely driven by software, most of which is commissioned by a pair of quasi-government agencies.

Freddie Mac and Fannie Mae were founded by the federal government to boost homeownership and now buy about half of all mortgages in America. As a result, they basically set the rules early on in the mortgage approval process.

They require lenders to use a particular credit scoring algorithm, “Classic FICO”, to determine whether an applicant meets the threshold to be considered for a conventional mortgage in the first place, currently a score of 620.

Launched over 15 years ago based on the 1990s database, Classic FICO is widely viewed as detrimental to people of color because it rewards traditional credit, to which they have less access than white Americans. It does not account for, among other things, on-time payments for rent, utilities, and cell phone bills, but will lower people’s scores if they fall behind on those bills and get sent to debt collectors. .

Yet Fannie and Freddie have resisted a flood of demands since 2014 from lawyers, the mortgage and housing industries, and Congress to authorize a newer model. They did not answer questions about why.

The approval process also requires a green light from Fannie or Freddie’s automated subscription software. Even their regulator, the FHFA, isn’t sure exactly how they decide, but some of the factors companies say their programs take into account can affect people differently based on their race or ethnicity, researchers have found.

For example, traditional banks are less likely than payday loan vendors to set up branches in neighborhoods with predominantly black populations. Payday lenders don’t report payments on time, so they can only hurt credit.

Concert workers who are people of color are more likely to report these jobs as their primary source of income, rather than a side activity, than white concert workers. It can make their income riskier.

Considering a plaintiff’s assets beyond the down payment, which lenders refer to as “reserves,” can cause problems for people of color. Largely due to intergenerational wealth and past racist policies, the typical white family in America today has eight times the wealth of a typical black family and five times the wealth of a Latino family.

The chairman of the business group representing real estate appraisers recently acknowledged that racial prejudice is prevalent in the industry, which sets property values ​​and has launched new programs to combat prejudice.

“If the data you provide is based on historical discrimination,” said Aracely Panameo, director of Latin American affairs at the Center for Responsible Lending, “then you are essentially cementing the discrimination on the other end.”

In written statements, Fannie said its software scans applications “regardless of race,” and both Fannie and Freddie said their algorithms were assessed for compliance with fair loan laws, internally and by the FHFA and the Ministry of Housing and Urban Development. HUD said it asked the pair to make changes accordingly, but would not release details.

The lender of Crystal Marie and Eskias McDaniels denied that race had anything to do with their refusal. In an email, LoanDepot vice president of communications Lori Wildrick said the company follows the law and expects “fair and equitable treatment” for every candidate.

The couple refused to give up after the loan officer told them the mortgage had not worked and asked their real estate agent for help. Crystal Marie’s employer sent several vouching emails.

At around 8:00 pm the day before the initial closing date, Crystal Marie received an email from the lender: “You are cleared to close. She still doesn’t understand how she got to yes, but she was overjoyed.

“It means so much to me, as a black person,” said Crystal Marie, who said her family descended from slaves in neighboring South Carolina, “to own property in a place where there is not that long ago you were a property.

“It’s so important.”

• This story was reported by The Markup, and the story and data was distributed by The Associated Press.

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