How Automated Communications Monitoring Works Across Messaging and Voice

Automated communications monitoring works by capturing, normalizing and analysing communications data to allow for risk review against compliance frameworks. By flagging suspicious or potentially non-compliant communications before they evolve, messaging and voice monitoring gives firms more foresight to catch and handle miscommunication or policy violations before they escalate or are spotted by regulators. 

Despite being an established compliance requirement, the end-to-end process has grown more complex over the years due to the growing number of conversations moving between platforms and off official channels. While this makes the process harder for compliance teams, so does the fact that not every alert establishes misconduct.

The role of automation has therefore only grown in importance. Pre-screening and wider data capture has become an integral part of the compliance process, enabling firms to confidently identify exactly which messages warrant individual review, without overwhelming their teams with administrative burden

Key Takeaways:

• Automated data monitoring converts communications into searchable, analysable data
• For voice-based communications, transcription is typically required before text-based analysis can be applied. The accuracy of this is integral in identifying risks.
• Data enrichment and contextual analysis can help improve the accuracy of the automated communications monitoring process
• Cross-channel surveillance helps reconstruct activity that spans multiple communications
• Alerts still require appropriate human investigation and compliance workflows

What is automated communications monitoring?

Automated communications monitoring uses software to continuously capture and analyze messages across email, internal messaging platforms, phone calls and social chats.

It typically works though a combination of rule-based keyword (lexicon) detection, although Global Relay goes beyond this with a specialized chain of thought process within our generative AI.

This enables the review of messages in their entirety, making alert decisions based on full contextual understanding. For compliance teams, the automation acts as a triage – allowing firms to review only the meaningful communications rather than reading everything manually.

Which Communication Channels Can Be Monitored Automatically?

Most business communication channels can be monitored automatically, although the techniques for capture and analysis differ:

Channel	Capture Format	Monitoring Approach
Email	Journaling or API-based (known as Connectors) to capture messages with attachments, time stamps, recipients etc	Lexicon and keyword screening, attachment scanning, AI-based risk scoring, with sender – recipient analysis to flag external or restricted contacts
Messaging platforms like whatsapp	API-based Connectors or through enterprise apps like the Global Relay app	Conversation-level analysis across threads, with detection of off-channel behavior and keyword alerts on text and shared media
Social media	API-based Connectors for Facebook, TikTok, X and Youtube to capture instant messages and post data	Monitoring of business and employee accounts for promotional, misleading, or confidential content, using keyword and AI classification
SMS	API-based Connector that captures tamper-proof records while enabling separation of personal and business texts	Keyword and phrase detection with rules-based alerts, plus checks for unapproved or personal-device use
Voice calls	API-based Connector that captures raw audio files and automatically translates and transcribes into written communications	Speech-to-text transcription followed by lexicon, sentiment, and AI analysis, with audio review for flagged calls
Trading communications	API-based Connector for Trading System Support covers live capture and legacy data migration, or record trading messages time-synced to trade records	Surveillance for market abuse, collusion, and insider dealing, with comms correlated to trading activity and order data
Collaboration platforms such as slack	API or export capture of channel messages, direct messages, edits, deletions, files, and reactions in structured formats such as JSON	Contextual thread analysis, keyword and AI detection, and monitoring of file sharing and channel membership changes

How Does Automated Communications Monitoring Work?

There are nine key stages of automated communications monitoring:

1. Capture
2. Normalize
3. Transcribe
4. Enrich
5. Analyze
6. Detect
7. Alert
8. Investigate
9. Preserve

Capture

Communications capturing involves real-time data ingestion of messages from the chosen channel into the capturing system. This includes the messages themselves, plus the metadata around them, such as the time sent, sender and recipient details, and links or attachments (later used in enrichment).

From a regulatory standpoint, automating the immutability of communications is integral – firms have the choice to do this through WORM-compliance or an audit-trail alternative under SEC 17a-4.

Normalize

Normalization involves mapping the data within communications to a standardised schema, ensuring that all the information required to make the decision has actually been collected.

For example, for voice comms, this might include the automatic raising or lowering of volume levels. For social media messages, displaying the text contexts, author, recipient, time stamps and channel in a spreadsheet-style format to ensure that each attribute has been captured, and that the system can later ‘read’ the messages without error.

Transcribe

Automatic communications transcription focuses on turning voice communications into their equivalent written messages in real-time. In some regulated industries, such as healthcare, this may also include the redaction of sensitive health information (PII) to protect the privacy of patients.

Enrich

Automating the enrichment phase for communications monitoring means adding the all-important context to messages. Metadata must be captured at source to enable data completeness. It reduces noise within the data as it makes a marked difference in the number of false positives or negatives during analysis.

Analyze

Automatic analysis evaluates the meaning of the communications against an organization’s risk profile. More primitive systems may analyze words individually using a rules-based approach, but this tends to lack nuance and may miss cases of intentional deception. Instead, using AI enables firms to understand messages within context and go beyond their identified risks. This provides the ability to surface alerts for threats that are unplanned, but still meet risk scoring guidelines. 

Detect

Automatic detection in communications monitoring is the categorisation of communications between acceptable and risky. Automated solutions typically use risk scoring to do this: comparing the level of risk within the communication to the level deemed ‘acceptable’ by your organisation.

The automation element ensures that detection occurs as soon as a suspicious message is analysed. 

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Alert

Alerts for communications monitoring use automation to deliver a higher level of recall and more precise alerts for complex, ambiguous and context-dependent communications  – including attempts to avoid surveillance. For example, our generative AI explains why an alert is raised, indicating where potential risk lies. The step-by-step chain of thought is displayed alongside each alert, providing greater transparency into how the decision was made.

Investigate

Communications investigations involve bringing a human-in-the-loop to make a judgment call: does the communication violate regulations or internal policies? Automation can help with queue routing: streamlining your workflow by routing policy alerts to the right people based on language, geography, corporate function, and more.

Preserve

Preservation is the final step of the automated communications monitoring process, and is triggered by the decision to investigate or ignore the communication against an organization’s risk profile. Automated systems can help meet compliance requirements – including securing the immutable messages in the eDiscovery system to be held for the regulator’s required time period.

How Are Voice Communications Monitored Differently From Text?

The main differences between voice communication monitoring and text-based messages are due to the way the information is first captured – audio files versus text:

• Transcription is required for voice communications to convert spoken word to text, enabling the same baseline for rules and AI models
• Firms must then make text searchable in order to locate specific terms within the eDiscovery legal hold or respond quickly to regulatory requests and exams
• Speaker information is required to be captured for extra context during analysis against the risk framework, attributing each statement to the right person
• Additional processing may also be required for audio files to reduce background noise, normalise accents, and confirm the accuracy of audio transcription

What Is Cross-Channel Communications Surveillance?

Cross-channel surveillance of communications means connecting related activity over multiple messaging systems to provide full context for analysis. For example, an advisor may:

1. Receive a message on social media requesting a phone call
2. Hold a voice conversation on the phone
3. Acquire the individual’s email address and move subsequent conversations to electronic channels

For firms, it’s typically easier to use a single, unified platform that can capture information immutably across all potential channels, than have to patchwork related conversations together manually. This also means that alerts can be surfaced with full context, reducing the chance of false positives.

What Can Automated Communications Monitoring Identify?

From suspicious patterns to policy violations, accurate communications monitoring can effectively identify any suspicious activity or violation, as long as firms feed the right rules into it. The technology doesn’t automatically determine guilt or regulatory breaches – instead, it reveals the key data that can help a compliance reviewer confidently make that decision, much faster than manual detection.

Automated Monitoring vs Communications Archiving: What’s the Difference?

The difference is that automated monitoring is the active analysis of communications for potential risk, whereas communications archiving refers to the preservation of communications.

Factor	Automated Monitoring	Communications Archiving
Primary purpose	Answers ‘is there anything we need to act on?’	Answers ‘what was said and done?’
Data scope	Focuses on flagged or high-risk communications data that may require intervention	Focuses on securely, immutably storing the communications in an easily-navigable format (regardless of risk)
Outputs	Alerts, risk scores and case files for review	Audit trails and retention controls
Use cases	Identifying market abuse, misconduct or policy breaches	Responding to regulator requests, litigation holds and investigations
Team involvement	Human reviewers triage and escalate alerts	Compliance, legal and IT retrieve records when required
Regulatory role	Demonstrates supervision of employee conduct	Satisfies record-keeping and retention obligations

What Should Firms Look for in an Automated Monitoring Platform?

When evaluating automated monitoring platforms, the regulatory considerations go far beyond user experience and price.

Channel coverage, for example, is one of the most important factors. Put simply: does the platform cover all of the communication channels your teams use, or would your investment also require a patchwork solution to integrate outside channels into the system?

Similarly, teams often find comparing the analysis process is helpful. Some providers rely on rules-based keyword matching only, which can limit alert accuracy as context is not always included. For voice communications in particular, this context is integral in determining meaningful interpretation, especially when audio files are noisy, low volume or pick up multiple voices.

System auditability is another consideration. Looking for firms that have experience in the regulated area, and directly with the regulators who govern your organization will provide a level of confidence that automations and integrations fit an examiner’s needs.

Turning communications into information that compliance teams can monitor and investigate

Effective communications monitoring is not simply the scanning of messages. Instead, it requires careful capture, understanding and connection across channels to add meaning – the all important context that reviewers make their final decisions on.

Automated compliance systems work in the background to turn those communications into contextual data, allowing teams to only monitor and investigate the alerts that actually carry risk. Prevent alert fatigue, increase operational efficiency and meet regulatory demands by choosing Global Relay’s secure Surveillance.

FAQs

What is automated communications monitoring?

Automated communications monitoring uses technology to capture, analyze, and flag risky or non-compliant content within messages. It uses rules, keywords and AI to ensure alerts are meaningful and presented with full context, ready for compliance review.

How are voice communications monitored for compliance?

Voice communications like calls or voice notes are recorded, transcribed (and possibly translated) into text, and then analyzed using the same models applied to written messages. Metadata capture is key: such as who actually says what in a conversation. Flagged calls are typically reviewed as both text and audio to confirm what was actually said, preventing noise from impacting investigation volumes.

Can compliance software monitor voice and messaging together?

Yes, modern compliance platforms capture and analyze voice, chat, email, and other channels in a single system, so conversations can be reviewed in one place.

What is cross-channel communications surveillance?

Cross-channel communications surveillance links related conversations across multiple messaging platforms, such as a chat, a call, and an email. This gives reviewers a complete picture of a conversation or behavior pattern, enabling a more accurate triage decision.

What happens after communications monitoring generates an alert?

Alerts are typically reviewed by a human. Communications monitoring systems should present alerts with all the necessary information and context to help the reviewer either close it or escalate it for an investigation. All decisions are also automatically logged to generate an audit trail for regulatory review.em to identify potential policy violations or misconduct. Archiving supports recordkeeping obligations, and surveillance supports supervisory obligations.