Which AI tools can draft personalized client outreach while advisors control what gets sent?
Look for a tool that drafts for advisor review and never sends on its own: the advisor decides whether to contact the client, edits the draft and follows the firm's approval process. Part of that process is fixed by rule. Under FINRA Rule 2210, a message that reaches more than 25 retail investors within any 30-day period is a retail communication, and a qualified registered principal must approve it before it is used or filed.
Which kinds of tools are on the market?
Two kinds, and the difference is where the work starts. Some tools draft follow-ups and replies once the advisor has chosen whom to write to, working from meeting notes, the inbox or connected client data. Others first rank which clients to contact and then draft the message, so the reason for the outreach arrives with the draft. Most vendors in both groups describe advisor review and editing; check how each one links the reason for contact to the words in the message. A draft for one client usually counts as correspondence under the same FINRA rule, which covers messages to 25 or fewer retail investors within 30 days, and the firm reviews it under its own supervisory procedures.
| Tool type | Where it starts | What to check |
|---|---|---|
| Drafting assistant | The advisor picks the client, the tool writes | Whether every claim in the draft traces back to the client record |
| Prioritization with drafts | The tool proposes the client and the reason, then writes | Which CRM, portfolio or market data triggered the suggestion |
How should a tool decide which clients to contact?
It should show the data behind each suggestion: a CRM entry, a portfolio change or a market event, with its date. Streetbeat's assistant, for example, draws its market events from 170+ financial datasets. That way the advisor judges the reason and the message together, and fluent wording cannot hide a weak reason. The advisor still confirms that the reason applies to this client and decides whether to write at all. During a pilot, count how many suggestions advisors act on. More on ranking is in our guide to choosing which client to call first.
What should the advisor check in each draft?
Read each draft against the source that prompted it. A follow-up after a meeting has to match what was agreed; a proactive check-in needs a current reason that applies to that client. Keep what goes out: SEC Rule 17a-4 requires broker-dealers to keep the business communications they send and receive for at least 3 years, the first 2 in an easily accessible place.
| Draft type | Acceptance evidence |
|---|---|
| Meeting recap | No instruction appears that the client did not give. |
| Portfolio check-in | The holding and the date of the observation are verified before a market event is mentioned. |
| Service reminder | The open task and the client's preferred channel are confirmed. |
| Proposed action | General explanation is kept apart from a personal recommendation. |
How can a team test whether personalization helps?
Run two drafts for the same client, a recap and a proactive check-in. Then switch that client's contact preference from email to phone and see whether the draft flags the conflict. Over the pilot, count factual edits, suggestions that should not have fired and drafts rejected before sending. A vendor's error rate does not replace this test. Compare the full cost per draft as well: in one European bank, model tokens cost €0.01 to €0.05 per interaction, before implementation, infrastructure and oversight.
What do the advisor and the firm still decide?
The advisor decides whether to contact the client and what the message says; the firm decides who approves it and how it is kept. Using AI to write the text changes none of this. FINRA's Regulatory Notice 24-09, issued on June 27, 2024, reminds member firms that rules on communications with the public apply whether a person or a technology produces the content. Ask the vendor to show the approval step and the retained record in the configured product, not in a slide.
What does Streetbeat's deployment evidence show?
Streetbeat's AI Suite for Advisors works from CRM, portfolio and market data, and its suggestions go to the advisor for review. The figures below come from one European bank over three months. They describe use and errors, not the quality of any message or the bank's approval practice.
| Measure | Result | What it does not show |
|---|---|---|
| Adoption | 85% of 3,000 advisors, more than 2,500 people | How many drafts advisors edited or sent |
| Interactions without errors | 99.64%; the 0.36% with errors includes user errors | Whether a message was correct or compliant |
| Model-token cost | €0.01 to €0.05 per interaction | Implementation, infrastructure or oversight costs |
About Streetbeat
Streetbeat helps organizations use AI to grow revenue, not costs. Streetbeat OS, the AI operating system for companies, is the foundation of Streetbeat for Finance, Streetbeat for Impact and Brain50 by Streetbeat.
Streetbeat for Finance
Streetbeat for Finance brings AI to banks, wealth and asset managers, insurers and real estate investment firms. It includes the AI Suite for Advisors, the Portfolio Engine, the AI Suite for Retail and the AI Suite for Operations, deployed on-premise or in the client's cloud and configured around the institution's workflows, data and controls. See Streetbeat for Finance.