Hiring more minority loan officers could help people of color secure significantly more home loans and address one of the biggest factors driving the racial wealth gap, new research finds.
In the white-dominated US banking industry, minority borrowers’ applications are less likely to be completed and approved, but when minority loan officers shepherd those applications, approval rates increase significantly, says Adi Sunderam, the Willard Prescott Smith Professor of Corporate Finance at Harvard Business School, in the working paper, “The Impact of Minority Representation at Mortgage Lenders.”
Loan officers seem to be having an important influence on mortgage outcomes.
“Loan officers seem to be having an important influence on mortgage outcomes,” Sunderam says. “The most surprising finding in the paper is the fact that minority officers are approving more minority borrowers and those borrowers are defaulting less.”
Before recent interest rate hikes, American homeowners had been reaping the benefits of record home prices, cashing out amid a buying frenzy. However, data from the National Association of Realtors showed that these transactions involved primarily white buyers and sellers, leaving people of color out of a crucial means of wealth building.
The national dearth of minority loan officers is considerable. In 2019, just 15 percent of mortgage loan officers were minorities, compared to 39 percent of the total US population, write Sunderam, along with W. Scott Frame of the Federal Reserve Bank of Dallas, and Erik J. Mayer and Ruidi Huang of Southern Methodist University.
Closing the gap between white and minority loan officers may help change that pattern, the researchers find. That has big implications for minority access to credit and the lending industry’s racial makeup of loan officers—a job that’s become more nuanced in a largely automated mortgage origination process, Sunderam says.
Loan officers are critical to the process
Loan officers play an important role for would-be borrowers, particularly in properly filling out paperwork and documentation needed in the application process, but sometimes also in pushing for consideration and approval. A loan officer’s role may be especially critical for applicants who may not tick all the conventional boxes, like having a robust credit score, proof of assets, and verifiable income streams.
The minority officers are particularly helpful in identifying creditworthy minority borrowers with atypical application profiles.
“There are lots of people who are creditworthy borrowers, but don't have W-2s. And if you don't have a W-2, it's going to be extra work to document your income up to the standard that is required,” Sunderam says. That type of “soft” information can make a difference for loans that require human discretion—applications that the automated system sends back for further analysis by a loan officer.
Minority loan officers may also be able to spot more creditworthy non-white borrowers versus white loan officers and automated systems, the researchers say.
“The minority officers are particularly helpful in identifying creditworthy minority borrowers with atypical application profiles,” Sunderam says.
The authors used three main datasets for their analysis: The Nationwide Mortgage Licensing System, since loan officers must be either federally registered or state licensed through the system; mortgage applications via confidential data from the Home Mortgage Disclosure Act maintained by the Federal Reserve System for 2018 and 2019; and Federal Housing Administration-insured mortgage originations from 2012 to 2018 for loan performance data.
They further parsed findings using US Census data and ZIP codes to match loan officers, mortgages, specific lenders, and applicants. The researchers matched first and last names and geographic data to ascribe race or ethnicity for the loan officer, identifying people as white, Black, Hispanic, or Asian. They then pinpointed 255,000 active loan officers for the year 2019.
To parse the “soft” information that minority loan officers rely on, Sunderam and colleagues focused on “high discretion” applications—those that automated underwriting systems neither approve nor reject.
Narrowing the default gap
The research team found minority applicants were about 3 percentage points less likely to be approved than white applicants working with the same white loan officer. Yet, for applications shepherded by minority loan officers, that difference shrank by 2 percentage points.
In addition, minority borrowers were 1.7 percentage points more likely to default than white borrowers working with the same white loan officer. That figure “all but” disappeared when the loan officer was also non-white, the researchers found.
That may not seem like a big gap, but the raw numbers are substantial. Of the 5.65 million mortgage applications studied, some 10 percent, about 565,000, were handled by minority loan officers.
The average applicant was 41 years old with $94,000 in annual income and a credit score of 725, requesting a loan of about $260,000.
Minority applicants had a 22 percent probability of being matched with minority loan officers, the authors found. Meanwhile, white applicants had a 95 percent probability of working with a white loan officer.
More minority officers could help even the playing field
If lenders hired more minority loan officers, that could go a long way toward closing the wealth gap among applicants, the authors say.
“Our back-of-the-envelope calculations suggest that improving minority representation among loan officers could close nearly half of the gap in access to mortgage credit between white and minority borrowers,” they write.
The findings also imply there may be similar disparities with other types of borrowing, such as small business loans, Sunderam says. However, there’s less data available to dig into that slice of the industry, he notes.
“We're doing this in a setting that is pretty automated, where there are lots of basic numbers that are going to determine the decision,” Sunderam says. “With something like small business lending, it's much less automated and much more bespoke, it's natural to think that these effects might be even bigger.”
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Feedback or ideas to share? Email the Working Knowledge team at hbswk@hbs.edu.
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