Signals are behavioral and intent patterns that Chordia's Compass engine identifies across customer conversations. Each signal represents something specific that happened — or didn't happen — during an interaction. Unlike keyword matching or sentiment scores, signals are grounded in the structure of the conversation: what was said, in what context, and what it means for your operation.
sig.required_verification_completed

Required Verification Completed

What This Signal Detects

Detect whether any program-required verification steps were completed (e.g., KBA executed, standard verification completed) before proceeding with sensitive actions.

This evaluation considers both identity verification completed prior to account specific or sensitive content event and required verification missing event to build a complete picture of what happened in the conversation.

Why It Matters

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 required verification completed 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.

How It Works

Compass analyzes the full context of the conversation to determine whether required verification completed 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.

What Teams Do With This

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.