How InferTrust™ helps financial institutions demonstrate fair lending compliance when AI is involved in credit decisioning.
The Equal Credit Opportunity Act (ECOA) and the Fair Housing Act prohibit discrimination in credit transactions. When AI models are used in credit decisioning, institutions must demonstrate that the models do not discriminate on prohibited bases and that adverse action notices accurately reflect the reasons for denial.
AI credit models can produce discriminatory outcomes through proxy variables, training data bias, or complex feature interactions that are not immediately apparent. Regulators increasingly expect institutions to demonstrate not just that they tested for bias, but that they have ongoing monitoring and governance in place to detect and address discriminatory patterns.
InferTrust™ (Patent Pending) Financial captures the decision event for every AI-assisted credit determination: the model version, the input features evaluated (as a hash), the confidence score, the decision action (FIN_APPROVE, FIN_DENY, FIN_FLAG, FIN_ESCALATE, FIN_HOLD), and the policy governing the decision. This creates a verifiable dataset for fair lending analysis that cannot be retroactively modified.
When an AI model contributes to an adverse credit decision, ECOA requires specific adverse action notices. InferTrust™ records document exactly what the model evaluated and what action was taken, supporting the institution's ability to provide accurate and verifiable adverse action reasons.