FINRA AI Audit Evidence for Supervisory Reviews

A FINRA examiner selects client email WM-1847. The archive contains the approved email, but the firm's AI register shows only a monthly total for the writing assistant. Nobody can connect the communication to the representative's prompt, the model output, the approved email, or the principal's review. FINRA AI audit evidence has to resolve that chain with contemporaneous records. I would treat a polished dashboard with no event-level joins as decoration. The useful package starts with a frozen population and lets the reviewer choose the row.

TL;DR

• Freeze the AI event and communication populations before sample selection.
• Join each selected event to identity and input; destination and output; policy decision; review and approval; and the retained business record.
• Test denials and exceptions, changes and integrity, plus historical retrieval alongside permitted traffic.
• Give gateway records bounded credit: they prove routed request decisions, while the firm retains supervisory and recordkeeping responsibility.

Freeze the population before the reviewer samples

FINRA says its rules remain technology neutral and apply when a member uses GenAI in its business, including proprietary tools and embedded features, along with third-party technology. The current FINRA artificial intelligence topic page also says the page creates no new legal requirements. Start the evidence package with that source status, then define the review population around the business use under examination.

For a communications review, export every AI-assisted draft linked to retail and institutional communications, plus correspondence during the period. Add every denied call and policy exception, along with every timeout and missing-identity event. For an AI-assisted supervisory process, include the alerts reviewed by the tool and the generated summaries, plus the human dispositions and underlying records. Preserve rejected drafts and escalations.

Freeze the manifest before selection. Give each row a stable identifier and UTC timestamp; application and business use; associated person or agent and model destination; outcome and source-record locations. Internal audit or the examiner can then pick samples without the control owner curating the cleanest green rows.

Reconstruct one supervisory event

FINRA Regulatory Notice 24-09 connects GenAI supervision to Rule 3110, which requires a supervisory system reasonably designed for the member's business. For GenAI used inside supervision, FINRA says policies and procedures should address technology governance and model risk management; data privacy and integrity; reliability and model accuracy. Those statements shape the evidence question. They create no separate AI rulebook.

For a selected event, begin with the originating user or agent and the application. Add the business purpose and input reference. Record the provider and exact model endpoint; output reference and policy version; decision and any redaction. Then join the event to the principal's review and final disposition under the firm's written supervisory procedures.

A shared API key identifies the technical caller. The evidence package still needs the person or agent on whose behalf the call ran. The post-authentication gap explains this distinction. IAM proves account and role assignment; the application supplies the identity and workflow context used at the AI boundary.

Tie AI-assisted communications to retained records

Rule 2210 applies content standards to communications produced by a person or a technology tool, a point FINRA repeats in Notice 24-09. The selected sample should therefore connect the AI event to the exact communication that was approved and sent. Keep the draft and edits; approval and distribution class; audience and channel; send timestamp. Preserve the record category and retention schedule selected by legal or records management.

The SEC's current Rule 17a-4 recordkeeping text requires originals of communications received and copies of communications sent relating to the broker-dealer's business, including covered communications with the public, for at least three years with the first two years in an accessible place. Paragraph (f) permits an audit-trail alternative or non-rewriteable, non-erasable storage. Under the audit-trail route, the system preserves modifications and deletions; timestamps and actor identity when applicable; information needed to recreate the original record.

Treat the routed AI event as supporting supervisory evidence. Records counsel decides when it is itself a required broker-dealer record and which retention rule applies.

Test integrity and historical retrieval

A retention configuration shows design intent. An old, reviewer-selected record proves operation. Retrieve one sample near the start of the retention window and produce both a human-readable copy and a usable electronic export. Recreate the original after a staged modification. Verify the communication and approval, the AI event and identity record, and the policy version share a traceable correlation chain.

Then challenge custody. Copy a staged event and alter its model destination. Run the documented integrity check and preserve the failed result. Attempt deletion with an application administrator role. Keep the rejection event and access-control evidence. The audit log chain of custody guide describes the independent write and custody pattern behind this test.

Run the retrieval exercise without the engineer who built the integration. A binder tab marked AI Evidence should lead another reviewer to the source records and query, the export and integrity result, and the owner. If the join works only after a Slack message to one developer, the control remains operationally fragile.

Package exceptions and missing joins

Include at least one denial and one approved exception. Add a failed review, if the period contains one, plus its remediation and retest. Show bypass findings such as an application that can call a provider directly. Also include an embedded AI feature with opaque model records and a browser session outside the managed route. Assign each gap an owner and interim measure, plus a due date and closure artifact.

Separate the evidence owners. Compliance owns the interpretation of FINRA scope and the written supervisory procedure. A registered principal owns the review outcome. Records management owns the record category and retention, plus legal hold and the production process. Procurement owns third-party evidence rights. Security owns routed traffic controls and evidence-store access. Internal audit owns sample independence.

This package adds operational evidence to the firm's required books and records. It never transfers Rule 3110 responsibility to a model vendor or an HTTP gateway. AI audit trail requirements by regulation provides a reusable event field set, while the FINRA package adds the communication and supervisory-procedure joins, including principal approval.

DeepInspect

DeepInspect sits between authenticated users or agents and LLM endpoints on HTTP routes the firm directs through it. It evaluates application-supplied identity and workflow context; applies content and destination policy; inspects the response; writes a signed, tamper-evident decision record.

That event can supply the request-level row in a FINRA evidence package. The firm still owns routing completeness and identity proofing; principal review and record classification; retention and legal hold; production. Opaque embedded inference and direct browser use need separate evidence. Book a technical deep dive at deepinspect.ai.