RandomGuy
06-13-2019, 04:06 PM
Elizabeth Warren may be running for president, but she hasn't stopped doing her whole Being A Senator thing, either. Which is why Warren is asking the heads of various agencies that regulate banks and financial services to explain what they intend to do about a problem with financial technology programs that have largely automated a lot of loan decisions. You see, a study published in October found that while systems like Quicken Loans have the potential to eliminate discrimination in lending, by removing the potential for loan officers' biases to affect lending decisions, in actual practice those algorithms still result in higher interest rates for black and Latinx borrowers, even when their credit scores are exactly the same as white customers.
Yes, we have made the robots racist.
The study, "Consumer-Lending Discrimination in the FinTech Era" (today we learned the buzzword "FinTech" for "financial technology"), was published by scholars at UC Berkeley's law school and its Haas School of Business, and aimed at determining whether FinTech lending fulfilled one of its promises: Could removing human loan officers eliminate bias from lending decisions? The authors found some surprising mixed results: While computerized loan decisions actually did eliminate bias in whether loans were approved, the loans that were approved resulted in higher costs for minority borrowers, even when the data were controlled for borrowers' credit scores.
"It's a surprise finding — because there's no human," said Robert Bartlett, a law professor at the University of California, Berkeley and a co-author of the study.
The researchers found that minorities paid 5.3 basis points extra in interest with online mortgage applications, little different than the 5.6 additional points they shell out with the overall set of lenders.
In other words: on a $300,000 mortgage, an African-American or Latino applicant would need to pay just under 1 percent — or around $2,000 more upfront in "discount points" or prepaid interest -- to secure the same mortgage rate as a white applicant, Bartlett said.
Each year, Latino and African-American borrowers pay between $250 million and $500 million extra in mortgage interest, the study said.
As to why that's happening, that appears to be the result of other factors used in creating the algorithms for "strategic pricing" of loans. Exactly what those factors are, Bartlett said, can be hard to identify since the programs are a proprietary "black box" used by the companies.
One potential explanation, however, is that online lenders utilize variables other than the traditional financial ones like credit score; they might be factoring in a borrower's geography or education level to price their loans, Bartlett said. [...]
[The] increasing use of "big data," in algorithmic lending, Bartlett said, could deepen discrimination further.
For example, the high school someone attended might predict their default rate. But it could predict their ethnicity, too.
https://www.wonkette.com/elizabeth-warren-financial-tech-discrimination
Yes, we have made the robots racist.
The study, "Consumer-Lending Discrimination in the FinTech Era" (today we learned the buzzword "FinTech" for "financial technology"), was published by scholars at UC Berkeley's law school and its Haas School of Business, and aimed at determining whether FinTech lending fulfilled one of its promises: Could removing human loan officers eliminate bias from lending decisions? The authors found some surprising mixed results: While computerized loan decisions actually did eliminate bias in whether loans were approved, the loans that were approved resulted in higher costs for minority borrowers, even when the data were controlled for borrowers' credit scores.
"It's a surprise finding — because there's no human," said Robert Bartlett, a law professor at the University of California, Berkeley and a co-author of the study.
The researchers found that minorities paid 5.3 basis points extra in interest with online mortgage applications, little different than the 5.6 additional points they shell out with the overall set of lenders.
In other words: on a $300,000 mortgage, an African-American or Latino applicant would need to pay just under 1 percent — or around $2,000 more upfront in "discount points" or prepaid interest -- to secure the same mortgage rate as a white applicant, Bartlett said.
Each year, Latino and African-American borrowers pay between $250 million and $500 million extra in mortgage interest, the study said.
As to why that's happening, that appears to be the result of other factors used in creating the algorithms for "strategic pricing" of loans. Exactly what those factors are, Bartlett said, can be hard to identify since the programs are a proprietary "black box" used by the companies.
One potential explanation, however, is that online lenders utilize variables other than the traditional financial ones like credit score; they might be factoring in a borrower's geography or education level to price their loans, Bartlett said. [...]
[The] increasing use of "big data," in algorithmic lending, Bartlett said, could deepen discrimination further.
For example, the high school someone attended might predict their default rate. But it could predict their ethnicity, too.
https://www.wonkette.com/elizabeth-warren-financial-tech-discrimination