Baloise Fraud Shield
by Baloise · Primary insurer
Anomaly detection platform that scores claims for fraud likelihood using network analysis and behavioural patterns, flagging suspicious cases for special investigation.
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Business context
- Purpose of use
Detect and prevent fraudulent claims earlier in the lifecycle.
- Value chain steps
- Fraud detection and preventionClaims management
- Insurance branches
- Motor vehicle insuranceProperty insuranceLiability insurance
- Application scope
- Internal only
- Business criticality
- Business critical
- Country or market unit
- SwitzerlandBelgium
Value and impact
- Added value category
- Cost reductionRisk reduction
- Added value estimation
Targets a measurable uplift in detected fraudulent claims value.
- Estimated weekly case volume
- 6,200
- Time to value (months)
- 8
- Competitive advantage gain
Graph-based network detection of organised fraud rings.
- Quality gain
Higher precision reduces false accusations against honest customers.
Technical details
- AI category
- Anomaly detectionMachine learning and predictive analytics
- AI platform provider
- Databricks Mosaic AI
- Cloud provider
- Amazon Web Services
- Technology stack
- DatabricksSparkGraph analytics
- Interfaces used
Claims system event stream
- Architectural insights
Streaming feature pipeline feeding a gradient-boosted scoring model.
- Automation level
- 3/5
- Estimated IT difficulty
- 4/5
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
Special investigations unit reviews every flagged case before action.
- Data used
Claims data, payment records, third-party fraud indicators.
Metadata
- Development type
- Minimum viable product
- Go-live date
- Dec 1, 2024
- License model
- Hybrid
- Original source
- https://www.baloise.com/insights
Community
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