Die Mobiliar logo

Mobiliar Damage Estimator

Award-winningAging

by Die Mobiliar · Primary insurer

Market unit: Switzerland

no ratings

Computer vision model that estimates property and natural-hazard damage from customer-submitted photographs to accelerate settlement after weather events.

Computer visionMachine learning and predictive analyticsProperty insuranceNatural hazards insurance

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AI capability and maturity

AI capability level

UnderstandGenerateReasonDecideActCollaborate

Capability Maturity Score (CMS)

5 / 6

Business Adoption Score (BAS)

4 / 6

AI Development Index (ADI)

20 / 36

See more information and theoretical background

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

Community

Average rating

0.0 · no ratings

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