Credit decisions must comply with ECOA and fair lending laws. InferTrust™ creates cryptographic proof of each model output and decision action so lenders can de
AI-assisted credit decisioning is among the most heavily regulated applications of artificial intelligence. The Equal Credit Opportunity Act (ECOA), Fair Credit Reporting Act (FCRA), and fair lending requirements mandate that credit decisions be explainable, non-discriminatory, and documented. As AI models become more sophisticated, the challenge of meeting these requirements grows, particularly around adverse action notices that must explain why credit was denied.
For each AI-assisted credit determination, InferTrust™ Financial captures the credit model version and feature set, the scoring methodology and policy thresholds, the resulting decision (approve, deny, counteroffer, or refer to manual underwriting), the adverse action reason codes generated by the model, and the complete downstream review chain. These records are immutably bound into a cryptographic chain.
When regulators examine an institution's fair lending practices, they evaluate individual credit decisions against the institution's stated policies. InferTrust™'s records enable examiners to verify that each AI-assisted credit decision followed the configured model, applied the correct policy, and produced appropriate adverse action explanations. This decision-level verifiability goes beyond what traditional model governance documentation provides.
Federal Reserve SR 11-7 guidance on model risk management requires institutions to validate and monitor models used in decision-making. InferTrust™'s continuous decision records support SR 11-7 compliance by providing verifiable evidence of model behavior in production, enabling ongoing validation that the model operates within its approved parameters.