FINRA Put Hallucinations in Your Next Exam.

In October 2025, Deloitte admitted that generative AI had helped write a government compliance report, and then refunded part of its fee after the report turned out to be full of fake citations. A Big Four firm, hired specifically to be right, caught shipping invented sources to a national government.

Two months later, on December 9, 2025, the Financial Industry Regulatory Authority (FINRA) published its 2026 Annual Regulatory Oversight Report and, for the first time, gave generative AI its own dedicated section. Hallucinations are named explicitly: instances where a model generates information that is inaccurate or misleading, yet is presented as factual. The report tells firms that ongoing human monitoring of model outputs is essential, and it points to supervisory frameworks with comprehensive documentation, output logging, and model tracking, not a one-time compliance check.

The report is guidance, not a new rule. But that is exactly the point: FINRA's rules are technology neutral, and Regulatory Notice 24-09 already confirmed that supervision, recordkeeping, and communications standards apply in full to AI-assisted work. On the RIA side, the SEC applies the Advisers Act the same way and put AI on its exam priorities. Nothing in the rulebook needed to change for the exposure to be real. Your next exam will simply ask what your supervision of AI looks like, and expect you to show it.

The tools guess. That is measured, not alleged.

When the fintech company Investing in the Web put financial questions to ChatGPT, it gave wrong or misleading answers 35% of the time: 65% of answers were correct, 29% were incomplete or misleading, and 6% were flat wrong. In the first preregistered, peer-reviewed audit of professional legal research tools, Stanford found even premium AI platforms hallucinated on 17% to 33% of queries. And in 2024, researchers published a formal argument that hallucination cannot be eliminated from large language models. It is not a defect a better model will fix. It is how the technology works.

For an advisor, the failure modes write themselves. A hallucinated RMD deadline in a client email. An invented IRS threshold in a planning memo. A confident, wrong summary of a fund's expense ratio on your website at 11pm. Each one arrives fluent, well-formatted, and indistinguishable from a correct answer, until a client acts on it or an examiner reads it.

Advisors already know this. The file does not show it.

Advisor360's 2026 Connected Wealth Report surveyed 300 advisors: 74% now treat AI as a help to their practice, and 93% said they want the final say over anything an AI tool produces. The instinct is exactly right. The problem is proof. Wanting the final say is not the same as being able to show, two years later, that you exercised it on the specific answer a client relied on.

That gap is where the exposure lives. Under FINRA Rule 3110 your supervisory system must be reasonably designed for the risks of the tools you use, and hallucination is now a named risk. A policy that says "we review AI output" with no record of who reviewed which output, when, is a claim. Examiners ask for records.

The SEC has already shown it will act on AI claims that do not match reality: in 2024 it fined Delphia and Global Predictions a combined $400,000 for overstating their use of AI. Saying you supervise AI you do not actually supervise is the same species of problem.

What the file needs to show.

Strip away the vendor language and the regulators are converging on four requirements. A human reviews AI output before a client can rely on it. The output is grounded in your firm's actual documents, not the open internet. When the system does not know, it says so instead of guessing. And every one of those review decisions leaves a record.

No generative chatbot meets the first requirement, because generation and delivery happen in one automated step. The answer reaches the client the moment it is composed. There is no gap where your final say can live.

That approval log is the artifact your file is missing. FINRA asked for ongoing monitoring, documentation, and output logging. Truebe produces all three as a byproduct of normal use. When the examiner asks how you supervise client-facing AI, the answer is a record, not a policy statement.

It runs on your server with your own API key. Truebe is never in the data path and never stores your client-facing content, which keeps your vendor diligence short and your client data where Regulation S-P expects it: under your control.

It also works inward. The same system runs a private research chat over the documents you upload: your compliance manual, WSPs, custodian procedures, planning checklists. You and your staff get answers drawn only from those documents, with the source cited and the exact passage shown. The consumer-chatbot shortcut, asking an unsupervised model to summarize a rule and trusting the answer, never has to touch your practice.

The bottom line.

A Big Four firm just refunded a government because AI invented citations in a compliance deliverable. FINRA responded by naming hallucinations in its exam playbook and asking firms to show documented human supervision of AI output. 93% of advisors already want the final say. The only question is whether your systems can prove you had it.

Truebe makes the final say structural: no unapproved answer ever reaches a client.