Automate Policy Change Requests for Your Insurance Brokerage

Brokerages rely on their Agency Management System, but its built-in tools are for record-keeping, not process automation. An email integration in Vertafore or Applied Epic can attach a client's email to their record, but it cannot read or understand the request. An Account Manager still must open the email, decipher the client's need, find the correct policy, and manually type the new information into dozens of fields. The AMS provides context, but the data entry burden remains entirely manual.

Consider a common scenario: a client emails, "We sold the Ford and got a 2024 Toyota Highlander, VIN XYZ. Please update our policy and send new ID cards." To process this, an agent spends 5 minutes navigating the AMS, deleting the old vehicle, adding the new one, and creating a follow-up task. For a brokerage handling 200 such changes a week, this single workflow consumes over 16 hours of skilled staff time on low-value data entry. This creates backlogs, frustrates clients, and introduces the risk of data entry errors that could affect coverage.

The structural problem is the gap between unstructured human language in emails and the structured data fields of an AMS. Generic email parsing tools can extract text but lack the insurance-specific logic to know that "Highlander" maps to the 'Vehicle Model' field for an auto policy. These tools cannot interpret context, handle PDF attachments like a new vehicle registration, or connect directly to core insurance platforms. They solve a piece of the problem without addressing the complete workflow.

The first step would be a process audit of your three highest-volume policy change types. Syntora would analyze 10-20 anonymized emails for each category to map the unstructured language to the specific fields in your AMS. The output of this discovery is a clear data schema and a fixed-scope proposal, confirming exactly what data points the system will extract for each request type before any code is written.

The technical architecture would use an AWS Lambda function to process incoming emails. The email's body and text from any attachments are sent to the Claude API with a prompt engineered to identify the client, policy number, and requested changes, outputting structured JSON. A FastAPI service then validates this JSON against a Pydantic schema that mirrors your AMS fields. This pattern, which we have implemented for complex financial document processing, ensures data is clean and correctly formatted before it ever touches your core system.

The delivered system would not replace your team but assist it. Extracted data would appear in a simple review queue showing the proposed change (e.g., 'Client: John Doe, Policy: AU-123, Action: Add Vehicle - 2024 Toyota Highlander'). Your account manager simply clicks 'Approve' to commit the change to the AMS via its API. This approach eliminates over 90% of manual typing while keeping an expert in control of the final approval, achieving the 30% overall time reduction target.