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Traps for the Unwary: Using Alternative Credit Data to Expand Credit Access to LMI Individuals and Underrepresented Communities | Goodwin

Traditional credit underwriting methods, which are generally based on credit reports, have not always successfully captured the full picture of a borrower’s ability to repay. It is.

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Banking Regulatory Scrutiny on Non Sufficient Funds

Banking Regulatory Scrutiny on Non Sufficient Funds
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Recent Fair Lending Cases Against Banks Large and Small

Recent Fair Lending Cases Against Banks Large and Small
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Furthering The Vision Of The Fair Housing Act, Federal Reserve Vice Chair For Supervision Michael S Barr, At Fair Housing At 55—Advancing A Blueprint For Equity National Fair Housing Alliance 2023 National Conference, Washington, D C

Furthering The Vision Of The Fair Housing Act, Federal Reserve Vice Chair For Supervision Michael S Barr, At Fair Housing At 55—Advancing A Blueprint For Equity National Fair Housing Alliance 2023 National Conference, Washington, D C
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AI in Credit Decision-Making Is Promising, but Beware of Hidden Biases, Fed Warns | Lowenstein Sandler LLP

To embed, copy and paste the code into your website or blog: As financial services firms increasingly turn to artificial intelligence (AI), banking regulators warn that despite their astonishing capabilities, these tools must be relied upon with caution. Last week, the Board of Governors of the Federal Reserve (the Fed) held a virtual AI Academic Symposium to explore the application of AI in the financial services industry. Governor Lael Brainard explained that “particularly as financial services become more digitized and shift to web-based platforms,” a steadily growing number of financial institutions have relied on machine learning to detect fraud, evaluate credit, and aid in operational risk management, among many other functions.[i]

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