ICBC – Using AI to Predict Customer Churn in Commercial Banking

Improved Churn Prediction By %

Optimize ROI across retention and acquisition activities

Executive Summary

This case study examines how NowVertical Group implemented AI solutions for ICBC, the largest bank in China, to predict customer churn in commercial banking. By leveraging advanced AI techniques like selective filtering, logistic regression, and clustering, ICBC improved its ability to identify customers at risk of churning.

Business needs

The Industrial and Commercial Bank of China Limited (ICBC) needed to improve potential churn identification. By accurately predicting churn, ICBC aimed to take proactive measures to retain customers and mitigate the negative impacts of customer attrition.

Business results after AI implementation:

  • Churn identification effectiveness improvement of greater than 15%
  • Better ability to proactively implement customer retention measures
  • Cost reduction by focusing on retention rather than customer acquisition
  • Ability to utilize data-driven decision-making Opportunity to improve operational efficiency

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