AI Policy Enforcement for Financial Services and Lending
Lenders and financial institutions use Corules to ensure AI credit decisions comply with ECOA, FCRA, and fair lending regulations. Every decision carries specific adverse action reasons, is replayable for regulatory examination, and is screened for disparate impact.
Das Problem
Lenders and financial institutions use Corules to ensure AI credit decisions comply with ECOA, FCRA, and fair lending regulations. Every decision carries specific adverse action reasons, is replayable for regulatory examination, and is screened for disparate impact.
Regulatorischer Kontext
ECOA requires specific adverse action notices on credit denials. FCRA governs use of credit report data. OCC guidance on AI in credit decisions requires explainability and auditability. CFPB has issued guidance requiring lenders to explain AI-generated credit denials with specific reasons.
Wichtige Entscheidungstypen
- Credit application approval and adverse action
- Loan modification and hardship program eligibility
- Credit limit increase and decrease decisions
- Fraud alert escalation and account suspension
- Underwriting exception approval
Verwandte Anwendungsfälle
Frequently Asked Questions
How does Corules satisfy ECOA adverse action requirements?
Every BLOCK decision returns specific violation codes that map to required adverse action reason language. The response includes the exact factor that caused the denial (debt-to-income ratio exceeded, credit score below threshold) — not a generic model score.
Can decisions be replayed for CFPB examination?
Yes. Every decision stores a normalized input hash and the policy version active at decision time. Regulatory examiners can reproduce any historical decision exactly.
Does Corules detect discriminatory patterns in credit decisions?
Corules enforces policy deterministically. The audit log enables disparate impact analysis — segmenting outcomes by protected class to identify if policy produces discriminatory effects. Corules identifies which rule is causing the pattern.