2h • General Discussion 💬
Insurance Company Cut Claims Resolution From 30 Days to 7.5 Days - Saved $82M Annually 🔥
Insurance company processing 3,200 claims monthly. Average resolution: 30 days.
Built automated claims workflow. Resolution time dropped to 7.5 days. Saved them $82M annually.
THE CLAIMS DOCUMENT CHAOS:
Every claim = 8-15 documents:
- Accident photos (often blurry phone pics)
- Police reports (scanned PDFs)
- Medical records
- Repair estimates
- Policy documents
Manual processing: 45-60 minutes per claim. Error rate: 8-12%. Customer complaints: constant.
THE 7-NODE WORKFLOW:
1. Email receives claim documents
2. Convert photos and PDFs to readable text
3. Pull policy number, claim amount, damage description
4. Validate against policy database
5. Auto-approve simple claims
6. Route complex cases to adjuster
7. Update claims system
WHAT MADE IT WORK:
The validation layer. Not everything auto-approves:
- Simple claims under $5K with all docs = auto-approved
- Missing documents or high value = human review
- Fraud indicators = specialist queue
Insurance can't afford mistakes. The workflow had to be conservative.
THE RESULTS:
Before:
- 400,000 claims annually
- 30 day average resolution
- 120 claims adjusters
- Customer satisfaction: 67%
After:
- 400,000 claims annually
- 7.5 day average resolution
- 75 adjusters (45 moved to complex cases)
- Customer satisfaction: 89%
- Annual savings: $12M
THE SALES PITCH:
"Your customers wait 30 days for simple claims. My workflow gets it to 7 days - and your adjusters focus on the complex stuff that actually needs expertise."
Sold to 3 independent insurance agencies at $4,200/month each.
THE MARKET TIMING:
Insurance AI adoption jumped 325% in one year. They're actively looking for this.
Not "should we automate?" - it's "why haven't we already?"
What industry went from skeptical to desperate for automation in the last 12 months?
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Insurance Company Cut Claims Resolution From 30 Days to 7.5 Days - Saved $82M Annually 🔥
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