Insurance
AutoClaims (Insurance Claim Triage)
An insurance company receives 500+ claims per day via email, web portal, and even fax.
The Problem (Before AI)
An insurance company receives 500+ claims per day via email, web portal, and even fax.
- A human reads each email, opens attachments, decides if it’s collision, theft, or weather damage.
- Then checks if police report, photos, and estimate are included.
- If missing docs, they email the customer and wait… often 7 days.
- Then assign to an adjuster based on zip code. Result: First response takes 3 days. Customers are angry. Staff is bored.
The AI Workflow (Step-by-Step)
| Step | What happens | AI’s job |
| 1 | Customer submits claim via email or portal | AI reads subject line + attachment names |
| 2 | System classifies claim type | AI trained on 10,000 past claims → outputs: collision / theft / weather / other |
| 3 | AI extracts key fields | Policy number, date of loss, location, description (using GPT regex) |
| 4 | Document completeness check | AI checks: is there a police report PDF? At least 2 photos? Repair estimate? |
| 5 | If missing anything → auto-email | AI drafts a friendly email listing exactly what’s missing + upload link. No human. |
| 6 | If complete → route to adjuster | AI matches location to team (e.g., zip code 90210 → West region, severe weather team) |
| 7 | Returning customer check | AI queries database: same policy number before? → flag previous claim history for fraud review |
Example Real Scenario
Customer submits: “My car was hit in the parking lot” with only one photo.
- AI sees: no police report, only 1 photo.
- Auto-email sent in 2 minutes: “Please upload the police report and 2 more photos showing damage from different angles.”
- Customer uploads → AI verifies → claim moves to adjust the same day.
Results
| Metric | Before | After |
| Time to first response | 3 days | 8 minutes |
| Missing docs resolution | 7 days | 4 hours |
| Staff time on triage | 40 hrs/week | 6 hrs/week |
| Fraud detection rate | Low | +35% (due to history check) |
[ Recent CASE STUDIES ]