AI Claims Call Center QA Agent

How Cassidy automates Call Center QA for Claims using AI

Step 1: Trigger on interaction completion

The Workflow activates when a call ends or a digital interaction closes—capturing the recording, transcript, and metadata including claim number, line of business, and disposition codes.

Step 2: Transcribe and extract key entities

Cassidy generates diarized transcripts (agent vs. caller), then extracts policy numbers, dates of loss, coverage terms, and sentiment indicators like frustration or escalation risk.

Step 3: Auto-score against your QA rubrics

The Workflow applies your insurer-specific scorecard—evaluating greeting, identity verification, empathy, required disclosures, information accuracy, and resolution handling—and generates a complete QA score for the interaction.

Step 4: Flag compliance and risk events

Cassidy checks for TCPA consent, GLBA/HIPAA adherence, PCI violations, missed timeline disclosures, and state DOI fair claims requirements—flagging any gaps with severity levels and remediation guidance.

Step 5: Generate coaching recommendations

Based on scoring gaps, Cassidy creates personalized coaching plans with call snippets, targeted micro-learning modules, and follow-up assessments tied to specific QA criteria.

Step 6: Update dashboards and alert stakeholders

Results flow to team and agent-level dashboards, with alerts routed to QA leaders, supervisors, or compliance teams via Slack, Teams, or email—keeping everyone informed during normal operations and CAT surges alike.