AI Group Underwriting Submission Agent

How Cassidy automates this using AI

Step 1: Trigger on new submission

The Workflow activates when a new RFQ, census file, or broker email arrives whether through your portal, a shared underwriting inbox, or API integration with your AMS.

Step 2: Extract and normalize submission data

Cassidy uses intelligent document processing to pull structured fields from PDFs, spreadsheets, and email attachments employer name, FEIN, group size, NAICS code, products requested, effective date, and plan design details normalizing everything to your internal data model.

Step 3: Perform clearance and deduplication

The Workflow checks for duplicate submissions, validates BOR/AOR authorization, confirms producer credentials against distribution agreements, and flags any territorial or compliance constraints before the case moves forward.

Step 4: Score completeness and generate RFIs

Cassidy evaluates submission quality missing census demographics, experience period gaps, absent plan documents and auto-generates a broker-ready RFI checklist while assigning a submission readiness score.

Step 5: Apply appetite and eligibility rules

The Workflow runs your codified appetite rules to determine disposition: auto-decline for out-of-appetite cases, route to STP for clean small-group submissions, or queue for underwriter review with exception flags and referral triggers.

Step 6: Prioritize and route to the right underwriter

Cassidy scores each case on appetite fit, winnability, premium potential, and SLA urgency then assigns it to the appropriate underwriter based on product line, region, authority matrix, and current workload, ensuring high-value opportunities surface first.

Step 7: Push clean data to your underwriting workbench

The Workflow delivers normalized submission data directly into your rating engine, Excel raters, or policy admin system complete with underwriting notes, referral documentation, and an audit trail ready for quote generation.