Research on Integrated Learning Algorithm Model of Bank Customer Churn Prediction

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With the rapid growth of Internet finance, competition within the banking industry has intensified significantly. To better understand customer needs and enhance customer loyalty, it has become crucial to develop a customer churn prediction model. Such a model enables banks to identify customers at risk of leaving, support data-driven business decisions, and implement strategies to retain valuable clients, thereby safeguarding the bank's interests. In this context, this paper presents a customer churn prediction model based on an ensemble learning algorithm. Experimental results demonstrate that the model effectively predicts and analyzes potential customer churn, providing valuable insights for retention efforts.