Customer Retention Management with Predictive Data Mining: An Indonesian Banking Case Study

Nguyen, Thi Thanh Thuy (2023) Customer Retention Management with Predictive Data Mining: An Indonesian Banking Case Study. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research project is centered on Indonesian bank’s customer loyalty. It employs innovative analytics techniques such as random forests (RF), Catboost, XGBoost (extreme gradient boosting), and deep neural networks to explore transactional data. To make the analysis more understandable, SHAP (SHapley Additive exPlanations) values should be utilized to provide actionable information from historical customer behaviors. The primary objective of the study is to determine the significant attributes of loyalty-based strategies and how it affects customer retention. SHAP values would benefit in analyzing the importance of features, making predictions at the individual basis, and comprehending features relationship. By conducting a comparative analysis and showing outcomes, the study seeks to discern critical factors that shape customers’ churn behavior. The research is significant in assisting banking service providers to develop customer-oriented strategies that will improve customer satisfaction and increase profits. The use of applying SHAP values shall make the analysis more transparent and clearer, enabling banks to make evidence-based decisions and prevent their customers from switching to a competitor. The findings show that XGBoost classifier is proposed as the most suitable one in predicting churner for customer retention strategy with actionable insights obtained.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Basilio, Jorge UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HG Finance > Banking H Social Sciences > HF Commerce > Marketing > Consumer Behaviour
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	18 May 2025 14:50
Last Modified:	18 May 2025 14:50
URI:	https://norma.ncirl.ie/id/eprint/7577

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