Where it fits
- A registered representative wants to publish a LinkedIn market update.
- A team is approving short-form X posts during volatile market news.
- A firm needs a defensible archive of approved and rejected social content.
- A compliance reviewer wants consistent checks across advisors and platforms.
Operational steps
- Classify the communication type, audience, platform, and whether it is retail, correspondence, or institutional communication.
- Scan for promissory, exaggerated, misleading, unbalanced, testimonial, ranking, or performance language.
- Attach rule references, reviewer notes, edits, disclaimers, approval status, and first-use dates.
- Archive the final content, supporting files, approvals, and platform metadata for later audit retrieval.
Common risks
- A post mentions return potential without comparable downside risk.
- Performance language is copied from a chart but the source and context are not preserved.
- A representative edits an approved post on-platform after approval.
- Social replies become business communications without capture or review.
How FINRAGuard AI fits the workflow
FINRAGuard AI gives teams a pre-publication review console, FINRA Rule 2210 mapping, flagged-language highlights, suggested rewrites, and an archive trail designed for supervisory review.