Customer churn prediction - A case study in retail banking

Teemu Mutanen; Sami Nousiainen; Jussi Ahola

doi:10.3233/978-1-60750-633-1-77

Customer churn prediction - A case study in retail banking

Teemu Mutanen, Sami Nousiainen, Jussi Ahola

VTT Technical Research Centre of Finland

Research output: Chapter in Book/Report/Conference proceeding › Chapter or book article › Professional

9 Citations (Scopus)

Abstract

This work focuses on one of the central topics in customer relationship management (CRM): transfer of valuable customers to a competitor. Customer retention rate has a strong impact on customer lifetime value, and understanding the true value of a possible customer churn will help the company in its customer relationship management. Customer value analysis along with customer churn predictions will help marketing programs target more specific groups of customers. We predict customer churn with logistic regression techniques and analyze the churning and nonchurning customers by using data from a consumer retail banking company. The result of the case study show that using conventional statistical methods to identify possible churners can be successful.

Original language	English
Title of host publication	Data Mining for Business Applications
Editors	Carlos Soares, Rayid Ghani
Pages	77-83
DOIs	https://doi.org/10.3233/978-1-60750-633-1-77
Publication status	Published - 2010
MoE publication type	D2 Article in professional manuals or guides or professional information systems or text book material

Publication series

Series	Frontiers in Artificial Intelligence and Applications
Volume	218

Keywords

Churn
customer churn
retail banking

Access to Document

10.3233/978-1-60750-633-1-77

Cite this

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Customer churn prediction - A case study in retail banking. / Mutanen, Teemu; Nousiainen, Sami; Ahola, Jussi.
Data Mining for Business Applications. ed. / Carlos Soares; Rayid Ghani. 2010. p. 77-83 (Frontiers in Artificial Intelligence and Applications, Vol. 218).

Research output: Chapter in Book/Report/Conference proceeding › Chapter or book article › Professional

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AU - Nousiainen, Sami

AU - Ahola, Jussi

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AB - This work focuses on one of the central topics in customer relationship management (CRM): transfer of valuable customers to a competitor. Customer retention rate has a strong impact on customer lifetime value, and understanding the true value of a possible customer churn will help the company in its customer relationship management. Customer value analysis along with customer churn predictions will help marketing programs target more specific groups of customers. We predict customer churn with logistic regression techniques and analyze the churning and nonchurning customers by using data from a consumer retail banking company. The result of the case study show that using conventional statistical methods to identify possible churners can be successful.

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KW - retail banking

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Customer churn prediction - A case study in retail banking

Abstract

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Keywords

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