_banking_&_insurance
The challenge
In order to proactively reduce customer churn, a leading insurance company wanted to create precise cancellation forecasts. The existing data warehouse (DWH), which was getting on in years, could no longer meet the increasing demands for speed and flexibility. In addition, outdated technologies led to high operating costs and made it difficult to implement new requirements.
Our approach
To meet these challenges, the DWH was comprehensively modernized. New data sources were integrated automatically and the database objects and ETL processes were redesigned. By using the Oracle Golden Gate replication solution, near-real-time data management was implemented, which made it possible to process current data almost in real time.
The solution
The modernization of the DWH led to a significant reduction in operating costs. The introduction of the new ETL technology improved performance and shortened the time-to-market for new requirements. Near-real-time data management enabled the company to predict cancellations based on data and initiate targeted customer retention measures. In addition, the DWH was adapted to the EU GDPR, ensuring compliance with current data protection guidelines.
The modernization also made it possible to integrate new data and implement numerous new features: The use of real-time data enables web clip analyses, while pattern recognition allows typical customer behavior to be analyzed before cancellations and countermeasures to be taken at an early stage. The modernized DWH also enables optimized recommendation management through the central storage and evaluation of relevant customer data. This means that individually tailored offers can be automatically suggested, such as family insurance for recently married customers.
Added value through DWH modernization:
- Early termination forecasts - identification of customers at risk of churning in order to implement targeted countermeasures at an early stage
- Increased customer loyalty - proactive measures based on current data to reduce customer churn
- Faster decision-making - near-real-time data management for immediately usable insights
- Cost efficiency - reducing operating costs by replacing outdated technologies
- Greater flexibility - faster implementation of new requirements thanks to optimized ETL processes
- GDPR compliance - ensuring compliance with current data protection guidelines
- Advanced customer analysis and targeting - use of web clip analysis, automated pattern recognition and improved recommendation management for individually tailored offers
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