AI Services · Service
Approval gates, audit trails, human review and recordkeeping built into AI-assisted workflows, mapped to the rules your firm actually answers to.
Short answer
AI compliance controls make sure AI output is reviewed, approved and kept before it reaches a client or an official record. We write the policy and data-flow maps, map them to FINRA, SEC, bank and insurance expectations that apply to you, then build the controls into Salesforce, HubSpot, Claude and ChatGPT so supervision happens inside the workflow.
Regulators have not written a separate rulebook for AI. They expect existing rules to apply: communications with the public are still communications, supervision still has to be reasonable, books and records still have to be kept, and models used in decisions still need governance. FINRA said as much in Regulatory Notice 24-09.
That makes the work practical. We find where AI touches a regulated activity, put a person and a record at that point, and make the record easy to produce. Your compliance team approves the controls; we configure and document them.
| Obligation | Where AI touches it | Control we build |
|---|---|---|
| FINRA Rule 2210 (communications) | AI-drafted emails, posts and client letters | Draft-only output, principal approval step for retail communications, approved-content library |
| FINRA Rule 3110 (supervision) | Reps using AI in client work | Usage policy, review queues, sampling and exception reports |
| SEC Rule 17a-4 and FINRA 4511 (books and records) | Prompts, outputs and AI-written notes | Retention settings, Compliance API or log export to your archive, CRM activity records |
| Regulation S-P | Client data sent to AI tools | Data classification, approved tools list, vendor terms review |
| Federal Reserve SR 26-2 (model risk) | AI used in decisions or scoring | AI register, validation evidence, change log per model or prompt |
| NAIC AI model bulletin (insurers) | AI in underwriting, claims or marketing | Written AI program, testing for unfair outcomes, vendor oversight |
| GDPR and UK GDPR | Personal data of EU or UK clients | Lawful basis, data-flow maps, retention limits, processor terms |
We configure and document controls. Legal interpretation and regulatory sign-off stay with your compliance and legal teams.
A policy that says "review AI output" means little if the CRM lets AI write straight to the record. Build the review step into the system.
To show what happened, you need the input, the output, the model and who approved it.
Models and prompts change. Re-run your evaluation set and log the result each time.
Our founder spent twelve years as COO of a wealth management firm before starting Vantage Point, and our practice serves financial services and other regulated industries. Supervision and recordkeeping are part of the design from day one.
Yes, with enterprise plans, approved data paths, human review of client-facing output and records kept under your retention rules. FINRA Regulatory Notice 24-09 reminds firms that existing rules apply to AI use, so the controls follow the same rules you already supervise.
They can, depending on what they contain and how they are used. We set up retention and export so you can keep what your compliance team decides must be kept, and keep AI-written notes in the CRM as normal activity records.
SR 26-2 is the Federal Reserve's April 2026 supervisory guidance on model risk management, which updates the expectations banks followed under SR 11-7. Banks using AI in decisions should keep an inventory, validation evidence and change records for those models.
No. We design, build and document controls. Your compliance and legal teams approve them.
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