Credit Decisioning

Credit decisioning refers to the use of algorithms, statistical models, and increasingly AI systems to decide whether a person or business gets approved for a loan, credit card, or other form of credit and on what terms. For enterprise governance teams, this is a high-stakes area because automated lending decisions fall under fair lending laws in the United States and similar consumer protection rules elsewhere, which require lenders to explain adverse decisions and avoid discriminatory outcomes. Regulators and courts have increasingly scrutinized whether models trained on historical data can produce disparate impact against protected groups, even when race or other protected traits are never explicitly used as inputs.

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