P&C Insurer Auto-Adjudicates 60% of Claims with AI on Snowflake + Azure
Document AI + ML triage automate routine claims and reduce average cycle time from 14 days to 2.
A national P&C insurer was processing 4M+ claims a year with average cycle times pushing 14 days. Adjusters spent 70% of their time on document review and data entry — work that did not require their expertise. Customer NPS was lagging the industry, and the operations leader had a board-level mandate to cut cycle time in half.
Apptad built a claims intelligence platform on Snowflake (data cloud) + Azure (compute and OpenAI). Document AI extracts and classifies submission packets, an ML triage model routes claims by complexity, and routine claims auto-adjudicate against policy rules with adjusters in an exception-only loop. We integrated with the insurer's core policy admin system without rip-and-replace.
Average cycle time fell from 14 days to 2 — a 7× improvement. 60% of claims now auto-adjudicate end-to-end, and adjuster time on routine work fell 80%, freeing them for complex losses. NPS lifted 22 points and combined ratio improved by a measurable 1.3 points.
The Numbers Behind the Story
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“Adjusters used to drown in paperwork. Now they focus on the claims that need a human — and our policyholders get answers in hours, not weeks.”
