Counterfactual Analysis: Explaining AI Decisions to Borrowers

You decline a CRE loan. Borrower asks: "Why?"

Traditional credit model: "Your loan-to-value ratio of 80% exceeds our 75% threshold."

AI model: ...silence. The model made the decision, but there's no simple rule to explain.

ACRGA-EXPLAIN uses counterfactual analysis. For every declined loan, answer: "What would need to change for approval?"

Example: "If your property valuation were $500k higher (vs. current $2.5M), your approval probability would increase to 85%."

This is actionable. The borrower understands what matters. The credit officer can discuss with the borrower whether revaluation is possible.

It doesn't explain *why* valuation matters (that's still opaque). But it tells the borrower what would change the decision.

This is practical governance for black-box models.

#Lending #Transparency #CREFinance