How Flawed Data Aggravates Inequality in Credit | Stanford HAI
AI offers new tools for calculating credit risk. But it can be tripped up by noisy data, leading to disadvantages for low-income and minority borrowers.
For aspiring home buyers, getting a mortgage often comes down to one talismanic number: the credit score. Banks and other lenders are turning to artificial intelligence to develop increasingly sophisticated models for scoring credit risk. But even though credit-scoring companies are legally prohibited from considering factors like race or ethnicity, critics have long worried that the models contain hidden biases against disadvantaged communities, limiting their access to credit. Now a preprint study in which researchers used artificial intelligence to test alternative credit-scoring models…
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