AI in Mortgage Compliance Research: How to Use It (and Where It Falls Short)

Raymond Snytsheuvel
Sep 25
5 min read

Mortgage compliance professionals spend hours reading statutes, rules, and examiner guidance. AI in mortgage compliance research promises to lighten that load by scanning dense regulations, surfacing citations, and pointing you in the right direction.

The catch? AI isn’t an experienced compliance officer. It can get you closer to an answer, but it won’t always give you one you can defend in front of an examiner. Used carelessly, it can generate fake citations, miss important context, or push you toward the wrong interpretation.

This article explores how AI can assist in compliance research, where it adds value, and why you still need to keep your professional judgment in the driver’s seat.

Mortgage professional using AI for mortgage compliance

Why Experience Still Matters

My daughter told me recently that she’s glad AI didn’t exist when she was in college—the temptation to lean on it would have been too strong. “You’d have passed but learned nothing,” I reminded her. “Exactly,” she said.

She’s right. Using AI for quick compliance research is tempting, but without judgment it can be useless in the right hands and damaging in the wrong ones.

Building compliance processes that fit federal, state, and local laws requires judgment–it’s more than just ticking boxes. There are a lot of nuances in those laws. When someone proudly shows me their AI-generated “compliance research,” I can’t help but channel Mandy Patinkin in The Princess Bride: “I do not think it means what you think it means.”

That’s the point: AI can surface information, but only your professional expertise can confirm whether it’s correct, defensible, and aligned with examiner expectations.

How AI In Mortgage Compliance Can Support Research

AI can serve as a guidepost in navigating complex laws and regulations. Used well, it can cut through noise and surface relevant information quickly. Here’s where AI can give compliance teams a lift:

Identify relevant statutes and regulations

AI can scan thousands of pages of legal text to pull the exact section of RESPA, TILA, or ECOA that applies to a specific lending question. This saves compliance officers hours of manual searching.

Assist in legal analysis

Some AI models can highlight how a law might apply to a scenario—flagging potential disclosure timing issues, fair lending risks, or adverse action requirements. It’s not legal advice, but it can point you in the right direction.

Provide rapid responses

With the right prompts, AI can generate answers in seconds that would take hours to draft manually. Sometimes it even delivers complete and accurate responses on the first try, giving compliance officers a head start.

Functional Controls Matter

The usefulness of AI is tied directly to how you use it. Poorly framed questions produce bad answers, while precise queries improve results.

Ask precise, citation-focused questions

If you ask “Tell me about TILA,” you’ll likely get vague summaries. If you ask, “What are TILA’s requirements for disclosure delivery timelines?” you’re more likely to get a useful, testable answer.

Limit the sources

AI works best when confined to reliable libraries—like federal regulations or internal compliance manuals. Opening it up to random internet content raises the risk of unreliable or non-authoritative answers.

Calibrate the scope

Broad queries may lead to hallucinations, where AI generates convincing but false content. Narrow prompts, on the other hand, can exclude necessary context. Balance is critical.

Think of it like Google Search in 2005: type in “mortgage compliance” and you’d drown in noise. Type in “Reg B adverse action notice content” and you’d get somewhere useful.

The Drunk Uncle Problem

AI is fast, but not flawless. In practice, it often behaves like a “drunk uncle”—sometimes insightful, other times wildly off track. Key risks include:

Incorrect citations

AI may fabricate citations or point to statutes that don’t exist. This is especially risky in compliance, where defensibility matters. I’ve seen this firsthand. Several times the tool surfaced a statutory or regulatory citation that plainly had nothing to do with my query.

Outdated information

Regulations change constantly. AI trained on old data may provide outdated answers unless paired with current legal libraries. In one instance, AI gave me what it claimed was an active statutory provision—but it had actually been repealed years ago.

That kind of error can make you second-guess your own research until you realize the issue lies with the tool, not your skills.

Misinterpretation and lack of nuance

AI tends to stick to the letter of the law, not the way regulators apply it in exams. That gap can create false confidence. In one case, AI correctly identified the elements that triggered a disclosure requirement and concluded no additional step was needed to show compliance.

But in practice, I knew an extra step was required—because without it, there would be no way to confirm proper timing (such as the notary date).

AI systems may differ

Not all AI platforms work the same way. You’ll likely need to test different systems (like Co-Pilot, Perplexity, ChatGPT, and others) to figure out which fits your compliance needs. And be prepared: AI systems may produce different or even conflicting answers.

In one case, one system confidently said a disclosure was required, while another said it wasn’t. This makes it even more important to cross-check results and not rely on a single tool.

The “arguing in circles” trap

AI can correct itself when prompted—but it may drift back to the same wrong answer just a query or two later. After asking AI to confirm a state regulatory requirement, it insisted a disclosure was required.

Only when the full statute was pasted in verbatim did it admit no disclosure was required. Yet within two more follow-ups, it contradicted itself again, insisting that a disclosure was required.

This is where the human factor makes all the difference. At some point, you stop arguing with your drunk uncle and move on without relying on their opinion.

Bottom line: AI can draft faster than you, but you still need to verify.

Ironically, AI in compliance research—at least for now—is best left in the hands of someone who has actually read virtually every state and federal law that could apply to mortgage lending, spotted the key nuances (“or” versus “and”), compared them against compendia and agency opinions, and made a sound policy call.

It’s like finishing a puzzle where the pieces are missing or don’t quite fit—but you still know what the picture is supposed to be. And if you’re still looking for the six-fingered man? Well, maybe AI can help with that.

Checklist for Compliance Teams

AI can help, but it must be managed with discipline and skepticism. If you’re experimenting with AI for research, follow these guardrails:

1. Ask the right questions – Precision improves accuracy.

2. Trust but verify – Cross-check outputs against the CFR, CFPB guidance, or state law.

3. Use as a supplement, not a substitute – AI speeds the process, but the compliance officer makes the call.

4. Stay patient and diligent – Expect clarifications, corrections, and refinement as you use the tool.

5. Know when to walk away – If AI has stopped being useful, abandon it and move forward with human judgment.

AI isn’t a shortcut to skipping your job—it’s a shortcut to finding where you should look next.

Partner with Loan Risk Advisors for Compliance AI

AI can speed up research, surface citations, and point you in the right direction—but it can’t replace your professional judgment. Think of it as a junior research assistant: fast, sometimes insightful, and occasionally off-base.

That’s where Loan Risk Advisors comes in. We help compliance teams cut through the noise, test vendor tools, and verify outputs against the regulations that matter most. Our goal is simple: make sure AI strengthens your oversight instead of creating new liabilities.

Contact us today to schedule a discovery call. Let’s turn AI into a tool you can trust—not another risk to manage.