WASHINGTON—Several potential fair lending risks associated with the use of artificial intelligence have been flagged by Federal Reserve Vice Chair for Supervision Michael Barr.
In remarks to a meeting in Washington, Barr said that while AI techniques such as machine learning “have the potential to leverage these data at scale and at low cost to expand credit to people who otherwise can’t access it…they also carry risks of violating fair lending laws and perpetuating the very disparities that they have the potential to address.”
‘Risks Are Amplified’
“Risks are amplified when a model is opaque and lacks a sufficient degree of explainability – the degree to which the bank can understand how data, variables, and other features inform the credit decisions,” he told the event.
Barr also pointed to appraisal bias and the risk of deficient collateral valuations, noting that these “can contain inaccuracies because of errors, omissions, or discrimination that affects the value of the appraisal, and the reconsideration of value may help to properly value the real estate.”
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