Mobiliar Damage Estimator
Award-winningby Die Mobiliar · Primary insurer
Computer vision model that estimates property and natural-hazard damage from customer-submitted photographs to accelerate settlement after weather events.
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Business context
- Purpose of use
Enable rapid, photo-based property damage assessment for policyholders.
- Value chain steps
- Claims management
- Insurance branches
- Property insuranceNatural hazards insurance
- Application scope
- Both
- Business criticality
- Business critical
- Country or market unit
- Switzerland
Value and impact
- Added value category
- Efficiency gainCustomer experience improvement
- Added value estimation
Speeds up settlement during high-volume catastrophe events.
- Estimated time savings
Around 20 minutes saved per property claim
- Estimated weekly case volume
- 3,100
- Time to value (months)
- 6
- Competitive advantage gain
Proven resilience during Swiss hail and flood event surges.
- Quality gain
More consistent damage estimates across regional adjusters.
Technical details
- AI category
- Computer visionMachine learning and predictive analytics
- AI platform provider
- Google Cloud Vertex AI
- Cloud provider
- Google Cloud Platform
- Technology stack
- Vertex AITensorFlow
- Interfaces used
Mobile claims app
- Architectural insights
On-device image pre-checks with cloud-based estimation.
- Automation level
- 3/5
- Estimated IT difficulty
- 3/5
Compliance and governance
- EU AI Act risk category
- High risk
- EU AI Act role
- Deployer
- Relevant policies
- EU Artificial Intelligence ActSwiss Federal Act on Data Protection
- Responsibilities
Regional claims managers validate AI estimates above a value threshold.
- Data used
Damage photographs, repair cost reference data, geospatial hazard data.
Metadata
- Development type
- Scaled application
- Go-live date
- May 1, 2023
- License model
- Hybrid
- Original source
- https://www.mobiliar.ch/medien
Community
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