How lenders are expected to evidence governance in AI-assisted credit decisions

Lenders increasingly rely on digital and AI-assisted systems across origination, underwriting, and portfolio management. As scrutiny grows, so does the expectation that governance of those systems can be evidenced clearly and defensibly.

Where governance scrutiny arises in lending

External review can be triggered by disputes, defaults, regulatory inquiry, investor diligence, or insurance review. In each case, reviewers focus on how decisions were governed at the time they were made.

Which systems influenced the decision?
Who was accountable?
What oversight existed?
What evidence can be produced?

The limits of model documentation and policy

Lenders often maintain extensive model documentation and policy frameworks. However, these do not always translate into evidence that satisfies external reviewers.

Common gaps include lack of time-stamping, unclear accountability, and difficulty demonstrating how governance was exercised in practice.

What defensible governance evidence looks like

Proportionate, evidence-based governance in lending typically includes:

Clear registers of decision-influencing systems
Named ownership and responsibility
Recorded governance and risk decisions
Time-fixed evidence of review and change

Why this matters for lenders now

As AI governance expectations mature, lenders are increasingly assessed on their ability to demonstrate oversight rather than assert it.

About this briefing

This briefing reflects conversations with credit, risk, and operations leaders navigating evolving expectations around AI-assisted decision-making.