Churn & Cross-sell Prediction in Leading Bank

Our client is a leading bank
  • Lack of integrated customer data
  • High churn ratios and lack of insight about the reasons of customer disengagement and inactivity.
  • Need for predictive action plan for high churn risk customers.
  • Need to deliver targeted offers for current customers from product portfolio.
  • Our scope was to design and implement an analytics datamart and apply churn prediction and cross-sell projects
  • Designed and implemented analytics datamart which integrates customer, product and sales transaction data
  • Built churn prediction models for credit cards
  • Built crossell model for consumer credit
  • Implemented an ML-Ops pipeline for managing machine learning models 
Tool Stack
  • SQL Server, Python, Airflow



Churn Model Coverage Ratio



Potential decrease in high churn risk



Potential increase in crossell offers