The secret bias hidden in mortgage- approval algorithms, Part II

“Using a database as opposed to human judgment can avoid influences by other forces, such as discrimination against minority individuals and red-lining,” Peter Maselli, then a vice president of Freddie Mac, told The New York Times when it launched its software, now called Loan Product Advisor. A bank executive told Congress that year the new systems were “explicitly and implicitly ‘color blind,'” since they did not consider a person’s race at all in their evaluations.
But, like similar promises that algorithms would make colorblind decisions in criminal risk assessment and health care, research shows that some of the factors Fannie and Freddie say their software programs consider affect people differently depending on their race or ethnicity. These include, in addition to credit histories, the prospective borrowers’ assets, employment status, debts, and the size of the loan relative to the value of the property they’re hoping to buy.
“The quality of the data that you’re putting into the underwriting algorithm is crucial,” said Aracely Panameño, director of Latino affairs for the Center for Responsible Lending. “If the data that you’re putting in is based on historical discrimination, then you’re basically cementing the discrimination at the other end.”
Research has shown that payday loan sellers usually place branches in neighborhoods populated mainly by people of color, where bank branches are less common. As a result, residents are more likely to use these predatory services to borrow money. This creates lopsided, incomplete credit histories because banks report both good and bad financial behavior to credit bureaus, while payday loan services only report missed payments.
Gig workers who are people of color are more likely to report that those jobs are their primary source of income — rather than a side hustle they’re using for extra cash — than white gig workers. Having multiple sources of income or unconventional employment can complicate the verification process for a mortgage, as Crystal Marie and Eskias McDaniels learned.
Considering an applicant’s assets beyond the down payment, which lenders call “reserves,” can cause particular problems for people of color. People with fatter bank accounts present a lower risk because they can more easily weather a setback that would leave others unable to pay the mortgage. But, 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. People of color are more likely to have smaller savings accounts and smaller (or nonexistent) stock portfolios than white people.
“This is a relatively new world of automated underwriting engines that by intent may not discriminate but by effect likely do,” said David Stevens, a former president and CEO of the Mortgage Bankers Association, now an independent financial consultant.
Not even home valuations are free from controversy. The president of the trade group representing real estate appraisers, who determine property values for loans, recently acknowledged that racial bias is prevalent in the industry and launched new programs to combat it.
“Any type of data that you look at from the financial services space has a high tendency to be highly correlated to race,” said Rice, of the National Fair Housing Alliance.
In written statements, Fannie said its software analyzes applications “without regard to race,” and both Fannie and Freddie said their algorithms are routinely evaluated for compliance with fair lending laws, internally and by the FHFA and the Department of Housing and Urban Development. HUD said in an email to The Markup that it has asked the pair to make changes in underwriting criteria as a result of those reviews but would not disclose the details.
“This analysis includes a review to ensure that model inputs are not serving as proxies for race or other protected classes,” Chad Wandler, Freddie’s director of public relations, said in a written statement. He declined to elaborate on what the review entails or how often it’s done.
No one outside Fannie and Freddie knows exactly how the factors in their underwriting software are used or weighted; the formulas are closely held secrets. Not even the companies’ regulator, the FHFA, appears to know, beyond broad strokes, exactly how the software scores applicants, according to Stevens, who served as Federal Housing commissioner and assistant secretary for housing at HUD during the Obama administration.
The Markup’s analysis does not include decisions made by Fannie’s and Freddie’s underwriting algorithms because, while lenders are required to report those decisions to the government, the CFPB scrubs them from public mortgage data, arguing that including them “would likely disclose information about the applicant or borrower that is not otherwise public and may be harmful or sensitive.” Lenders’ ultimate mortgage decisions are public, however. Borrowers’ names are not reported to the government, and addresses are not in the public data.
Fannie and Freddie declined to answer our questions about why their algorithms’ decisions are excluded from the public data but said in a 2014 letter to the CFPB that the revelation could allow their decision-making algorithms to be reverse-engineered.
Loan officers say the software’s decisions are mysterious even to them.
“When you run so many deals through the automated system, you’ll look at one deal that didn’t get an approval, and you just know that that’s a better client than someone else that might’ve gotten approved,” said Ashley Thomas III, a broker and owner of LA Top Broker, Inc., a minority-owned real estate agency and brokerage in South Los Angeles. “That lack of transparency in the technology is very concerning.”
The Community Home Lenders Association sent a letter to Fannie and Freddie in April complaining about unannounced changes to both of their underwriting software programs that members discovered when applicants who had previously been approved suddenly were denied.
Scott Olson, executive director of CHLA, said there’s no good reason to keep lenders in the dark: “The more transparent, the more clear the guidance is, the easier it is for borrowers to know what they need to do to be in a position to qualify.”
Earlier this month — and weeks after we began asking about its algorithms — Fannie announced in a news release that it would start incorporating on-time rent payments in its loan approval software starting in mid-September. When we asked about the timing of that change, spokesperson Katie Penote emailed The Markup a statement saying the company wanted prospective borrowers “to have this option as soon as possible” but was silent about what prompted it.
In addition to using Fannie’s or Freddie’s software, many large lenders also run applicants through their institutions’ own underwriting software, which may be more stringent. How those programs work is even more of a mystery; they are also proprietary.
When we examined the reasons lenders listed for denying mortgages in 2019, the most common reason across races and ethnicities, with the exception of Native Americans, was that applicants had too much debt relative to their incomes. When lenders did list “credit history” as the reason for denial, it was cited more often for Black applicants than white ones in 2019: 33% versus 21%.
When we examined the decisions by individual lenders, many denied people of color more than white applicants. An additional statistical analysis showed that several were at least 100% more likely to deny people of color than similar white borrowers. Among them: the mortgage companies owned by the nation’s three largest home builders.
The two principal laws forbidding housing and lending discrimination are the 1968 Fair Housing Act and the 1974 Equal Credit Opportunity Act. An alphabet soup of federal agencies can refer evidence of violations of these laws to HUD or the Justice Department for investigation, but referrals have dropped precipitously over the past decade.
Marcia Fudge, who took over HUD leadership earlier this year, told Axios in June that part of the reason Black ownership rates are so low in America is that “we have never totally enforced the Fair Housing Act.” In an email, HUD press secretary Meaghan Lynch told The Markup that Fudge intends to tackle “systemic discrimination in the housing and credit markets that is at the heart of the racial homeownership gap.”
“We do have laws that explicitly protect against discrimination, and yet you still see these disparities that you’re finding, so that suggests that we need better enforcement of existing laws and more investigations,” said Kevin Stein, deputy director of the California Reinvestment Coalition. “Agencies need to do a better job of ferreting out discrimination and taking serious action once they find it.”
Another key housing law, the federal Community Reinvestment Act (CRA) of 1977, allows the federal government to penalize lenders who fail to invest in low-income or blighted neighborhoods but make no requirements regarding borrowers’ race. Stein’s group has lobbied for the law to be reformed.
Lenders who violate fair lending rules can be punished with fines in the millions of dollars. Rep. Al Green, a Texas Democrat, has sponsored legislation wending its way through Congress that would make it a crime to engage in lending discrimination.
“Banks already have laws that punish people who commit fraud,” he said. “You can be imprisoned for — I hope you have your seatbelt on — 30 years. Why not have some similar law that deals with banks who are invidiously discriminating against people who are trying to borrow money?”
And some fair lending advocates have begun to ask whether the value system in mortgage lending should be tweaked.
“As an industry, we need to think about, what are the less discriminatory alternatives, even if they are a valid predictor of risk,” said David Sanchez, a former Federal Housing Finance Agency policy analyst who currently directs research and development at the nonprofit National Community Stabilization Trust. “Because if we let risk alone govern all of our decisions, we are going to end up in the exact same place we are now when it comes to racial equity in this country.”
Crystal Marie McDaniels said whatever effect race may have had on her denial, it wasn’t overt.
“I’m not sure you ever really know because there are no klansmen in our yard or anything — but it’s definitely something we always think about,” she said. “It’s just something that we always understand might be a possibility.”
The lender, loanDepot, denied race had anything to do with the decision. The company’s vice president of communications, Lori Wildrick, said in an email that the company follows the law and expects “fair and equitable treatment” for every applicant. “We take the issues raised by Ms. (McDaniels) very seriously and are conducting a thorough review of her concerns.”
Crystal Marie said buying a house was crucial for her because she wants to pass on wealth to her son someday, giving him an advantage she never had. So when the loan officer told her the deal wasn’t going to happen, she refused to give up.
With the help of their real estate agent and multiple emails from her employer on her behalf, she and her husband Eskias pushed back against the denial.
Around 8 p.m. on the night before the original closing date, Crystal Marie got an email from the lender: “You’re cleared to close.”
She still doesn’t understand how the lender went from a no to a yes, but she was relieved and elated.
“It means so much to me, as a Black person, to own property in a place where not that many generations ago you were property,” said Crystal Marie, who said she is descended from slaves in neighboring South Carolina.
She said her family has always had a fraught relationship with money. Some relatives were so mistrustful of banks that they’d insisted on dealing only in cash, she said, making it impossible to build up credit or wealth for future generations.
“It’s meant so much,” she said, “that we were able to go through this process and finally, eventually, be successful.”
This story was reported by The Markup and the story and data were distributed by The Associated Press.