Minority homebuyers face widespread statistical lending discrimination

November 15, 2018 by Laura Counts, University of California - Berkeley
Credit: CC0 Public Domain

Face-to-face meetings between mortgage officers and homebuyers have been rapidly replaced by online applications and algorithms, but lending discrimination hasn't gone away.

A new University of California, Berkeley study has found that both online and face-to-face lenders charge higher interest rates to African American and Latino borrowers, earning 11 to 17 percent higher profits on such loans. All told, those homebuyers pay up to half a billion dollars more in interest every year than white borrowers with comparable credit scores do, researchers found.

The findings raise legal questions about the rise of statistical discrimination in the fintech era, and point to potentially widespread violations of U.S. fair lending laws, the researchers say. While lending discrimination has historically been caused by human prejudice, pricing disparities are increasingly the result of algorithms that use machine learning to target applicants who might shop around less for higher-priced loans.

"The mode of lending discrimination has shifted from human bias to algorithmic bias," said study co-author Adair Morse, a finance professor at UC Berkeley's Haas School of Business. "Even if the people writing the algorithms intend to create a fair system, their programming is having a disparate impact on minority borrowers—in other words, discriminating under the law."

First-ever dataset

A key challenge in studying lending discrimination has been that the only large data source that includes race and ethnicity is the Home Mortgage Disclosure Act (HDMA), which covers 90 percent of residential mortgages but lacks information on loan structure and property type. Using machine learning techniques, researchers merged HDMA data with three other large datasets—ATTOM, McDash, and Equifax—connecting, for the first time ever, details on interest rates, loan terms and performance, property location, and borrower's credit with race and ethnicity.

The researchers—including professors Nancy Wallace and Richard Stanton of the Haas School of Business and Prof. Robert Bartlett of Berkeley Law—focused on 30-year, fixed-rate, single-family residential loans issued from 2008 to 2015 and guaranteed by Fannie Mae and Freddie Mac.

This ensured that all the loans in the pool were backed by the U.S. government and followed the same rigorous pricing process—based only on a grid of loan-to-value and credit scores—put in place after the financial crisis. Because the private lenders are protected from default by the government guarantee, any additional variations in loan pricing would be due to the lenders' competitive decisions. The researchers could thus isolate pricing differences that correlate with race and ethnicity apart from credit risk.

The analysis found significant discrimination by both face-to-face and algorithmic lenders:

  • Black and Latino borrowers pay 5.6 to 8.6 basis points higher interest on purchase loans than White and Asian ethnicity borrowers do, and 3 basis points more on refinance loans.
  • For borrowers, these disparities cost them $250M to $500M annually.
  • For lenders, this amounts to 11 percent to 17 percent higher profits on purchase loans to minorities, based on the industry average 50-basis-point profit on loan issuance.

"Algorithmic strategic pricing"

Morse said the results are consistent with lenders using big data variables and machine learning to infer the extent of competition for customers and price loans accordingly. This pricing might be based on geography—such as targeting areas with fewer financial services—or on characteristics of applicants. If an AI can figure out which applicants might do less comparison shopping and accept higher-priced offerings, the lender has created what Morse calls "algorithmic strategic pricing."

"There are a number of reasons that ethnic minority groups may shop around less—it could be because they live in financial deserts with less access to a range of products and more monopoly pricing, or it could be that the financial system creates an unfriendly atmosphere for some borrowers," Morse said. "The lenders may not be specifically targeting minorities in their pricing schemes, but by profiling non-shopping applicants they end up targeting them."

This is the type of price discrimination that U.S. fair lending laws are designed to prohibit, Bartlett notes. Several U.S. courts have held that loan pricing differences that vary by race or ethnicity can only be legally justified if they are based on borrowers' creditworthiness. "The novelty of our empirical design is that we can rule out the possibility that these differences are due to differences in credit risk among borrowers," he said.

Overall decline in lending discrimination

The data did reveal some good news: Lending discrimination overall has been on a steady decline, suggesting that the rise of new fintech platforms and simpler online application processes for traditional lenders has boosted competition and made it easier for people to comparison shop—which bodes well for underserved homebuyers.

The researchers also found that fintech lenders did not discriminate on accepting minority applicants. Traditional face-to-face lenders, however, were still 5 percent more likely to reject them.

Explore further: Financial education key to reducing student loan stress

More information: Consumer-Lending Discrimination in the Era of FinTech: faculty.haas.berkeley.edu/mors … h/papers/discrim.pdf

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17 comments

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Duude
3 / 5 (4) Nov 15, 2018
We've been down this road before. Just over ten years ago, the US was trying to bridge the gap with extremely lenient standards to getting a mortgage. The result was the biggest financial crisis of my lifetime.
Cusco
5 / 5 (1) Nov 15, 2018
No, they weren't trying to bridge any racial gap, they were exploiting the deregulation of the financial industry to game the system. By writing a mortgage for anyone who walked in the door, bundling them into securities, and convincing S&P and Moodys to rate them as AAA investments they carried out the largest financial fraud in history. Once a very minimal percentage of the extremely unqualified borrowers defaulted the entire thing fell apart and broke the world's economy.

Even Adam Smith declared that government needed to regulate business, because businessmen will **always** collude to the detriment of society.
MR166
not rated yet Nov 15, 2018
Cusco the banks were forced by the government to make sub-prime loans. The banks lied and offloaded these to the financial community as AAA bonds. Some Republicans tried to stop the sub-prime lending but were voted down.
Da Schneib
not rated yet Nov 15, 2018
@MR lies like usual. It was a financial fraud perpetrated by a Chinese national. No one's seen him since.

https://www.wired...p-quant/

Currently residing in Beijing. Need I say more?

https://uwaterloo...vid-x-li
MR166
not rated yet Nov 15, 2018
Da sometimes it is impossible to tell if you are serious or not. When you make loans to people without checking their income "Liar Loans" no analysis can turn them into AAA bonds.
Da Schneib
not rated yet Nov 15, 2018
@MR, it's obvious that you have trouble reading articles that are linked. It's impossible to tell if this is stupidity or trolling, and I don't care to guess.
MR166
not rated yet Nov 15, 2018
From the moment these bonds were created there was no doubt in the minds of the creators that they would default. That is why they sold them short while selling them to financial institutions. How can anyone analyze risk when the input data is false to begin with? The politicians both Dems and Republicans did absolutely nothing to punish the perps.
Da Schneib
not rated yet Nov 15, 2018
Bush held the SEC.

We done here?
MR166
not rated yet Nov 15, 2018
When the loans were created they asked the borrowers how much they earned. The answers were never checked and everyone knew that it was acceptable to make up any income figure that was needed to get the loan. OF COURSE all of these loans failed because they were based on lies. I know of people who brought homes, collected rents on the property and never made one mortgage payment while the courts protected them.
MR166
not rated yet Nov 15, 2018
"Bush held the SEC. "

Da it is obvious that you care about nothing other than the Democrats holding power. You care little for our laws.
Da Schneib
not rated yet Nov 15, 2018
I'm not part of gerrymandering, nor suing Republican-held departments to stop vote-counting.
szore88
not rated yet Nov 15, 2018
Everything for free for everybody! Yay!
szore88
not rated yet Nov 15, 2018
When the loans were created they asked the borrowers how much they earned. The answers were never checked and everyone knew that it was acceptable to make up any income figure that was needed to get the loan. OF COURSE all of these loans failed because they were based on lies. I know of people who brought homes, collected rents on the property and never made one mortgage payment while the courts protected them.


Welcome to socialism. Only goal? Destroy the economy, take it over and put everybody on welfare. But of course, you have to confiscate the guns first...
Da Schneib
not rated yet Nov 15, 2018
The loans were made by capitalists in their greed.

On Earth.
MR166
not rated yet Nov 15, 2018
"The loans were made by capitalists in their greed. "

Da why do you have such a hard time admitting the governments role in this debacle? Were you in a coma during those years? It was all part of the plan to make more loans to minorities.

If just once a progressive would admit that one of their plans did not work our as intended it would be a great milestone in political awareness.
NoStrings
not rated yet Nov 15, 2018
It appears they are talking about purely algorithmic evaluation of a loan risk and profitability, based on a borrower income, financial history, etc. After the fact, the study evaluated where the shoe dropped - that is, what categories of people were charged a higher interest.

This is essentially, proving that if the evaluation was based on lower socioeconomic status, and the minorities, excluding Asian and such, are typically in that bracket, the result is as it was found.

If default is more likely by some category of people, some bank resources are also spent on courts, repossessions, loss of money on the resale, a lot of things. While the no problem loans are just that - collecting monthly mortgage for the duration of home ownership.

A final result, that half a billion extra 'profit' may be actually a loss. Like, for example, your house insurance will cost more (hopefully) if it is positioned on a flood plain.
Da Schneib
not rated yet Nov 15, 2018
The Chinese figured the stupid banksters would believe anything, so they tried it out. Looks like it worked.

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