Allianz Suisse Subrogation AI
by Allianz Suisse · Primary insurer
Machine learning system that identifies recovery and subrogation opportunities in closed claims to recover costs from liable third parties.
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Business context
- Purpose of use
Recover more costs through systematic subrogation detection.
- Value chain steps
- Claims managementFinance and controlling
- Insurance branches
- Motor vehicle insuranceLiability insurance
- Application scope
- Internal only
- Business criticality
- Business operational
- Country or market unit
- Switzerland
Value and impact
- Added value category
- Revenue increaseCost reduction
- Added value estimation
Surfaces additional recovery opportunities missed by manual review.
- Estimated weekly case volume
- 4,100
- Time to value (months)
- 8
- Competitive advantage gain
Systematic recovery detection across the full claims book.
- Quality gain
More complete identification of recoverable claims.
Technical details
- AI category
- Machine learning and predictive analyticsNatural language processing
- AI platform provider
- Microsoft Azure AI Foundry
- Cloud provider
- Microsoft Azure
- Technology stack
- Azure MLText Analytics
- Interfaces used
Claims data warehouse
- Architectural insights
Batch scoring over closed claims with NLP feature extraction.
- Automation level
- 3/5
- Estimated IT difficulty
- 4/5
Compliance and governance
- EU AI Act risk category
- Limited risk
- EU AI Act role
- Deployer
- Relevant policies
- Swiss Federal Act on Data ProtectionEU Artificial Intelligence Act
- Responsibilities
Recovery team validates each opportunity before pursuit.
- Data used
Closed claims files, liability indicators, correspondence text.
Metadata
- Development type
- Minimum viable product
- Go-live date
- Mar 15, 2025
- License model
- Software as a service
- Original source
- https://www.allianz.ch/news
Community
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