Year: 2024
Type: article
Abstract: 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.
Authors: Shang Xinping, Wang Yi
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4404436697