We built an end-to-end "Zero-Touch Claims" pipeline that automated 80% of the claims lifecycle, from intake to payment, with human oversight only for complex or high-value cases.
Phase 1: Omni-Channel Smart Intake
We deployed an AI-powered claims bot across WhatsApp, the mobile app, and web portal. Policyholders could file a claim in under 3 minutes:
* AI: "I'm sorry to hear about the damage. Can you upload 3-4 photos of the affected area?"
* AI: "Thanks. Can you describe what happened in a few sentences?"
* AI: "Was a police report filed? If so, please upload it."
The AI used Computer Vision to automatically categorize damage severity (minor, moderate, severe) from photos and extracted key data from uploaded documents using OCR.
Phase 2: Instant Fraud Scoring
Every claim was instantly scored by a Machine Learning fraud detection model trained on 5 years of historical claims data and known fraud patterns:
* Cross-referencing claimant history (multiple claims in short period?)
* Geolocation analysis (was the phone at the incident location?)
* Photo metadata analysis (was the image taken recently or recycled?)
* Network analysis (is the claimant connected to known fraud rings?)
Claims scoring below 15% fraud risk were auto-approved for "fast track" processing.
Phase 3: Automated Estimation & Payment
For auto-approved claims (water damage, minor auto, etc.), the AI cross-referenced repair cost databases and local contractor rates to generate an instant estimate. If the policyholder accepted, payment was initiated via ACH within 24 hours—no human touch required.
Phase 4: Adjuster Workbench for Complex Cases
For flagged or high-value claims, adjusters received a pre-populated case file with the AI's analysis, fraud score breakdown, and recommended action. This reduced their review time from 2 hours to 20 minutes per case.
