Customer Churn Prediction in Banking Sector by Using ML Techniques
Title: Customer Churn Prediction in Banking Sector Using Machine Learning Techniques
Permalink: http://www.ijetjournal.org/customer-churn-prediction-banking-ml
Description: This paper explores machine learning techniques for predicting customer churn in the banking sector. It analyzes real-world datasets to compare algorithm effectiveness and highlights feature importance in predictive modeling.
Keywords: Customer churn, predictive modeling, machine learning, classification algorithms, IJET Journal
International Journal of Engineering and Techniques – Volume 10 Issue 2, 2024
Meetkumar Dilipbhai Kanani, Bhargav Dipakkumar Amin, Dr. Akil Z. Surti
Email: kananimeet34@gmail.com, bhargavamin2013@yahoo.in, dr.akilzsurti@gmail.com
Abstract
Customer churn is a significant challenge for businesses, leading to revenue loss. This study investigates machine learning techniques for churn prediction using real-world banking datasets. It compares algorithm performance, analyzes feature importance, and highlights how random forests outperform other models in predictive accuracy. The insights contribute to the advancement of customer relationship management strategies in the banking sector.
Keywords
Customer churn, predictive modeling, machine learning, classification algorithms, IJET Journal
How to Cite
Meetkumar Dilipbhai Kanani, Bhargav Dipakkumar Amin, Dr. Akil Z. Surti, “Customer Churn Prediction in Banking Sector Using Machine Learning Techniques,” International Journal of Engineering and Techniques, Volume 10, Issue 2, 2024. ISSN 2395-1303
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