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Customer churn forecasting
A dynamic churn prediction model for a leading Azerbaijani financial institution, identifying at-risk loan customers and driving targeted retention.
AI/ML
The challenge
The model had to stay responsive to changing customer behaviors and economic conditions, extract actionable insights from diverse datasets spanning transaction histories, demographics and market trends, and personalize loan products at scale across a vast customer base.
Our solution
- Engineered a dynamic churn prediction model tailored to evolving behaviors and market conditions.
- Extracted insights from transaction histories, demographics and market trend data.
- Refined and personalized loan offerings based on behavioral analysis.
- Integrated churn predictions with marketing and CRM workflows for proactive retention.
Results
- Reduced customer churn through the tailored prediction model.
- Attracted new clients via data-driven marketing strategies.
- Enhanced loan offerings, boosting satisfaction and cross-selling opportunities.
