86%
Overall Accuracy
Model correctly predicts 8 out of 10 customer outcomes with high reliability
30%
High Risk Threshold
Customers with probability above 30% require immediate attention from relationship managers
5
Key Risk Factors
Age, Germany residence, balance, activity status, and gender are primary churn predictors

Key Insights

Critical findings from the customer churn analysis

Age & Geography = Highest Risk

Older customers and those residing in Germany show significantly higher churn probability. German customers are more than twice as likely to leave compared to French customers.

Activity Status is the Strongest Lever

Customer activity status has the most dramatic impact on churn risk. Becoming inactive raises risk sharply, while returning to active status significantly lowers it.

Ignore These Factors

Tenure, credit card ownership, and estimated salary show no meaningful correlation with churn. Focus resources on the statistically significant factors instead.

Individual Risk Scores Available

Every customer receives a probability score between 0-1. Managers can rank customers by risk and focus on the top 10-20% most likely to leave.

High Balance ≠ Low Risk

Counterintuitively, customers with higher balances show increased churn risk. These valuable customers need special attention and personalized retention strategies.

Product Holdings Protect Retention

Customers with more banking products are less likely to leave. Adding products lowers risk, while losing products raises it significantly.

Strategic Recommendations

Actionable strategies for relationship managers to reduce customer churn

Focus on 7 Critical Factors

Prioritize age, activity status, Germany residence, gender, balance, credit score, and number of products. These statistically significant factors drive retention success.

Implement Tiered Strategy

High-risk customers (30%+) get direct outreach. Moderate-risk (15-30%) receive targeted offers. Low-risk maintain regular communication.

Keep Customers Active

Monitor activity status closely and re-engage inactive customers immediately. This single factor has the most dramatic impact on retention probability.

Cross-Sell Additional Products

Encourage customers to add more banking products. Each additional product significantly reduces churn risk and increases customer stickiness.

Special Attention for German Customers

German customers require enhanced relationship management due to their higher baseline churn risk. Implement region-specific retention programs.

Personalize High-Balance Customer Care

High-balance customers paradoxically show higher churn risk. Provide tailored conversations highlighting their value and financial goal support.