What is eComms Surveillance?
Electronic communications surveillance (eComms surveillance) is the systematic monitoring of business communications, including email, instant messaging, voice, social media, collaboration tools, and mobile messaging. The goal is to detect misconduct, enforce policy, and demonstrate compliance with regulatory obligations.
For regulated firms, eComms surveillance is not optional. Regulators, including FINRA, the SEC, and the FCA, require firms to supervise employee communications and maintain records that can be produced on demand. Surveillance is the mechanism that makes supervision meaningful. It’s more than a record-keeping function. It’s an active program for identifying risks before they become regulatory or reputational events.
What eComms Surveillance Covers
Modern surveillance programs must account for the full breadth of how employees communicate. That scope has expanded significantly as collaboration tools and consumer messaging apps have entered the workplace.
- Email — The foundational eComms channel and the most comprehensively governed
- Instant messaging and collaboration platforms — Microsoft Teams, Slack, Bloomberg Chat, Symphony, and similar tools are used for internal and external business communication
- Mobile messaging — SMS, WhatsApp, WeChat, Telegram, and other apps are increasingly used for client-facing communication, and are a primary source of recent regulatory enforcement action
- Voice — Recorded calls, voicemail, and meeting audio, including multilingual transcription for surveillance purposes
- Social media — Public and direct communication on platforms used for client outreach or market commentary
- Video conferencing — Zoom, Teams, and similar platforms where business discussions occur and, in some jurisdictions, must be captured
A surveillance program that covers email but not mobile messaging, or voice but not collaboration tools, will have gaps that regulators and bad actors will exploit.
What eComms Surveillance Is Designed to Detect
Surveillance programs are built around defined risk typologies. These are the categories of misconduct that regulators require firms to monitor for, and that compliance teams are accountable for identifying. Common typologies include:
- Market manipulation — Coordinated trading strategies, front-running, spoofing, and layering discussed or arranged via communications
- Insider trading — Sharing or acting on material non-public information
- Collusion — Coordination between traders, brokers, or counterparties at separate institutions
- Information barrier breaches — Communications that cross the boundary between a firm’s public-side and private-side employees
- Personal misconduct — Harassment, discrimination, and other conduct policy violations
- Off-channel activity — Use of unauthorized messaging platforms to conduct business outside the firm’s surveillance infrastructure
How AI Has Changed eComms Surveillance
Legacy surveillance systems used lexicon-based detection that included a list of keywords and phrases that, when found in a message, triggered a review alert. The approach is simple to implement and easy to explain to a regulator. It is also blunt. A message containing a flagged word in a compliance training context looks identical to one describing actual misconduct. False positive rates in legacy systems routinely exceeded 90%, leading to reviewer fatigue and reducing compliance teams’ capacity to identify genuine risk.
AI-Powered Surveillance Changes the Calculation in Three Ways
Contextual Understanding
Natural language processing (NLP) models analyze the meaning and intent of communications beyond their surface content. A message that uses no flagged keywords but describes a coordinated trading strategy can be identified as high-risk. A message that triggers a keyword in a clearly innocuous context can be deprioritized.
Behavioral Analytics
Machine learning models build baseline profiles of normal communication behavior for individual employees and relationships. Deviations from that baseline, such as unusual counterparties, atypical timing, and shifts in communication channels, surface as risk signals independent of message content.
Alert Precision
By combining contextual and behavioral analysis, AI surveillance platforms dramatically reduce false positive rates. Compliance teams review fewer alerts, but those they do review are more likely to represent genuine risk. Review resources are concentrated where they matter.
eComms Surveillance and the Regulatory Record
Effective surveillance is not just about detection. It is about documentation. Regulators examining a firm’s compliance program want to see that communications are being captured and that the surveillance program is operating as designed. It’s important that alerts are reviewed, cases are documented, and decisions are made and recorded consistently.
This is where eComms surveillance integrates with the broader GRC (Governance, Risk, and Compliance) framework. Surveillance generates the signals; supervision workflows process them; the audit trail demonstrates program effectiveness. Each layer depends on the others. A surveillance system without structured review workflows produces alerts that go nowhere. A supervision program without precise surveillance drowns reviewers in noise.
Synonyms and Related Terms
- Communications surveillance
- Electronic communications monitoring
- E-Comms monitoring
- Conduct surveillance
- Trade communications surveillance
- Communications compliance