Detect interactions where regulated financial advice, guarantees, or prohibited assurances are given.
This evaluation considers both agent financial advice or recommendation made event and agent guarantee or assurance made event to build a complete picture of what happened in the conversation.
Compliance gaps do not announce themselves. They sit quietly in your call recordings until an auditor or regulator comes looking. Manual QA catches a fraction of these moments. Automated detection ensures every interaction is evaluated, turning compliance from a sampling exercise into a measurable standard.
When regulated language risk is detected consistently, it often points to a training gap, a confusing process, or a script that agents are struggling to follow naturally. The signal does not just flag individual calls. It reveals patterns that help you fix the root cause.
Compass analyzes the full context of the conversation to determine whether regulated language risk occurred. This is not keyword matching or phrase detection. The evaluation considers meaning, sequence, and conversational dynamics to distinguish genuine instances from surface-level similarities.
The evaluation is calibrated to account for ambiguity. When the evidence is not strong enough to make a confident determination, the signal surfaces as unclear rather than being forced into a binary present-or-absent result. This means teams can trust the signal when it does fire.
Compliance teams monitor this signal across the full interaction volume to measure adherence rates and identify risk. A team running at 95% looks very different from one at 99.5%, and the difference is invisible without automated tracking.
Supervisors use it to identify which agents or teams need targeted coaching. The goal is not to punish misses but to understand why they happen and address the underlying cause, whether that is training, process confusion, or time pressure.
Audit and legal teams use the data as documentation. When regulators or internal stakeholders ask how compliance is maintained, the answer is grounded in data from every interaction, not extrapolated from a small sample.
This signal is part of Chordia’s Compliance Monitoring capabilities.
