Mortgage lenders do not have the luxury of waiting for AI regulations to be resolved. While states and Washington spar over who sets the rules, lenders remain fully responsible for how artificial intelligence is used in underwriting, servicing, marketing and fraud detection. The question is no longer as AI will be regulated; what matters is whether lenders are ready when critical scrutiny arises.
Here are three steps lenders should take now to protect themselves, scale responsibly, and avoid becoming a test case for regulators.
1. Build real AI governance, not just a policy document
AI risk management cannot live in a slide deck. Lenders need a formal governance framework that inventories every AI-powered tool in use, documents how models are trained, and defines who is accountable for results.
That includes understanding data sources, monitoring anomalies and biases, and identifying escalation paths when AI outputs impact borrower eligibility, pricing or disclosures. Regulators indicate that “we are dependent on a supplier” will not be an acceptable defense. If AI impacts a consumer outcome, lenders will bear the risk.
Equally important, governance must be operational, not theoretical. Compliance teams, legal, IT and business leaders need shared visibility into where AI is deployed, how decisions are made and how exceptions are handled in real time. When governance is disconnected from day-to-day workflows, problems only surface after harm has occurred, which is exactly when regulators and plaintiffs’ attorneys will start paying attention.
2. Rewrite supplier supervision before regulators do it for you
Most existing vendor contracts are not written for AI research. Lenders should now tighten their agreements to address training data ownership, audit rights, bias testing, explainability and data segregation.
State laws already require lenders to explain automated decisions and document risk assessments, even if AI is provided by third parties. If suppliers cannot provide transparency or test artifacts, lenders will be exposed. Supplier oversight is quickly becoming a core compliance function, no longer a purchasing activity.
This also changes the way lenders must assess technology partners in the future. AI readiness is about governance maturity. Suppliers that cannot demonstrate responsible model development, ongoing monitoring and regulator-ready documentation will slow lenders down rather than accelerate them. In a fragmented regulatory environment, the wrong supplier can become a compliance liability overnight.
3. Scale AI consciously, not everywhere at once
AI doesn’t have to be all-or-nothing. The smartest lenders are starting with lower-risk use cases such as document classification, workflow automation and fraud detection, while retaining human oversight for high-impact decisions.
This phased approach allows lenders to demonstrate responsible use, collect performance data, and refine controls before extending AI more deeply into lending and eligibility workflows. Automation reduces effort, but it doesn’t reduce responsibility.
It also creates a trail of evidence that regulators increasingly expect to see. By rolling out AI incrementally, lenders can document performance benchmarks, exception rates, override patterns, and fairness testing over time. That data becomes crucial if examiners don’t just ask for it What AI does it, but Why it was deployed, How it is checked and when people intervene.
Lenders that view AI adoption as a controlled program rather than a blanket rollout will be better positioned to defend the results as scrutiny increases.
Why mortgage AI means higher stakes
AI runs on data, and in mortgage lending that data is personal, sensitive and regulated. Compliance regimes such as RESPA, TILA and TRID require precision, explainability and strict timelines. Introducing AI into these workflows without governance does not eliminate the risks; it magnifies it. Small data errors can quickly become large-scale compliance violations.
This reality is driving increased regulatory scrutiny of automated decision-making, particularly in the areas of fair lending, transparency and consumer impact. Opaque models are no longer acceptable, and ‘black box’ explanations will not survive scrutiny.
A fragmented rulebook for now
In the absence of federal legislation, the states were the first to act. California expanded its privacy regime to include automated decision-making. Colorado has passed the nation’s first comprehensive AI law targeting high-risk systems, including credit eligibility tools. Other states are following suit, creating a patchwork of obligations that are difficult for national lenders to manage.
That fragmentation may not last. In December 2025, President Trump signed an executive order directing the federal government to establish a unified national AI framework and challenge state laws deemed to hinder innovation. A legal battle is likely, but the direction is clear: Federal standards will be forthcoming.
Compliance becomes a test of trust
AI regulation is entering a volatile phase. States assert their authority. Washington is pushing back. Courts will determine the boundaries. Despite all this, lenders remain responsible for the results.
In the AI era, compliance is no longer just about meeting technical requirements. It’s about trust among regulators, investors and borrowers. Lenders that act now, govern with purpose, and scale responsibly will not keep up on their own. They will help determine what compliant AI in mortgage lending will look like next.
Geoffrey Litchney is Managing Regulatory Counsel and Director of Compliance at Dark Matter Technologies. An expert in federal and state lending regulations, Litchney’s work focuses on transforming legal, regulatory and privacy requirements into practical, business-ready solutions that responsibly drive innovation. He can be reached at [email protected].
This column does not necessarily reflect the opinion of HousingWire’s editorial staff and its owners. To contact the editor responsible for this piece: [email protected].
Related
#steps #lenders #stay #ahead #regulations