Visana Churn Predictor
by Visana · Primary insurer
Predictive analytics model that identifies members at risk of cancellation and recommends targeted retention actions for the service team.
2 free views left this month
Business context
- Purpose of use
Reduce member churn through timely, targeted retention.
- Value chain steps
- Marketing and distributionCustomer service
- Insurance branches
- Supplementary health insurance
- Application scope
- Internal only
- Business criticality
- Business operational
- Country or market unit
- Switzerland
Value and impact
- Added value category
- Revenue increaseCustomer experience improvement
- Added value estimation
Targets reduction in voluntary lapse during the cancellation window.
- Time to value (months)
- 6
- Competitive advantage gain
Timely retention signals ahead of the Swiss cancellation deadline.
- Quality gain
Better targeted outreach instead of mass campaigns.
Technical details
- AI category
- Machine learning and predictive analytics
- AI platform provider
- Databricks Mosaic AI
- Cloud provider
- Microsoft Azure
- Technology stack
- DatabricksMLflow
- Interfaces used
CRM campaign integration
- Architectural insights
Monthly scoring batch with explainability for service agents.
- Automation level
- 2/5
- Estimated IT difficulty
- 3/5
Compliance and governance
- EU AI Act risk category
- Limited risk
- EU AI Act role
- Deployer
- Relevant policies
- Swiss Federal Act on Data Protection
- Responsibilities
Marketing and data protection jointly approve outreach use.
- Data used
Member tenure, interaction history, premium changes.
Metadata
- Development type
- Minimum viable product
- Go-live date
- Feb 15, 2025
- Estimated number of users
- 12,000
- License model
- Hybrid
- Original source
- https://www.visana.ch/news
Community
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