Prediction of bank credit customers churn based on machine learning and interpretability analysis

Prediction of bank credit customers churn based on machine learning and interpretability analysis

Nowadays, traditional machine learning methods for building predictive models of credit card customer churn are no longer sufficient for effective customer management. Additionally, interpreting these models has become essential. This study aims to balance the data using sampling techniques to forec...

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Bibliographic Details
Main Authors: Ying Li, Keyue Yan
Format: Article
Language:English
Published: AIMS Press 2025-01-01
Series:Data Science in Finance and Economics
Subjects:
customer churn
machine learning
shap
causal inference
r-learner
Online Access:https://www.aimspress.com/article/doi/10.3934/DSFE.2025002
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https://www.aimspress.com/article/doi/10.3934/DSFE.2025002

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