Customer Churn Prediction in Retail Banking using Predictive Analytics

Prakash, Rahul (2024) Customer Churn Prediction in Retail Banking using Predictive Analytics. Masters thesis, Dublin, National College of Ireland.

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Abstract

This research investigates the effectiveness of several machine learning models, Logistic Regression, Decision Trees, Random Forest, and also, XGBoost, in forecasting customer churn within the banking field. Achieving a high accuracy on the test dataset, the research highlights the potential of these models to efficiently recognize at-risk customers. Comprehensive performance metrics, including precision, recall, F1-score, and also, AUC, disclose the strengths and weak spots of each model, stressing the reliability of artificial intelligence techniques in boosting customer retention strategies. Even with the appealing results, the research study recognizes limitations associated with generalizability as well as dataset predispositions. It highlights the importance of targeted interventions based on model predictions as well as the assimilation of qualitative customer reviews for improved solution alignment. The results deliver valuable insights for specialists, advising that enhanced machine learning procedures may substantially maximize advertising and marketing initiatives and enhance customer satisfaction, while future research ought to explore added variables as well as boost model interpretability in real-world functions.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Nolan, Eamon 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 Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Retail Industry
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	04 Sep 2025 10:36
Last Modified:	04 Sep 2025 10:36
URI:	https://norma.ncirl.ie/id/eprint/8777

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