Comparative Analysis of Machine Learning Models for Customer Churn Prediction in the U.S. Banking and Financial Services: Economic Impact and Industry-Specific Insights

ISSN Print: 2327-7211
ISSN Online: 2327-7203
www.scirp.net/journal/jdaip
E-mail: [email protected]

Citations

"Comparative Analysis of Machine Learning Models for Customer Churn Prediction in the U.S. Banking and Financial Services: Economic Impact and Industry-Specific Insights"
written by Omoshola S. Owolabi, Prince C. Uche, Nathaniel T. Adeniken, Oghenekome Efijemue, Samuel Attakorah, Oluwabukola G. Emi-Johnson, Emmanuel Hinneh,
published by Journal of Data Analysis and Information Processing, Vol.12 No.3, 2024

has been cited by the following article(s):

No relevant information.

[1]	Real-Time Conversational Analysis Using LLMs for B2B E-Commerce Customer Value Management Engineering, Technology & Applied Science Research, 2026 DOI:10.48084/etasr.15797

[2]	Autoencoder-LSTM Ensembles for Predictive Analysis of Financial Churn Patterns 2025 International Conference on Emerging Smart Computing and Informatics (ESCI), 2025 DOI:10.1109/ESCI63694.2025.10988434

[3]	AI's Transformative Impact on Finance, Auditing, and Investment Advances in Computational Intelligence and Robotics, 2025 DOI:10.4018/979-8-3373-0129-7.ch002

[4]	Integrating Predictive Analytics with Customer Behavior Data in E-commerce Based on Machine Learning Model International Journal of Advanced Research in Science Communication and Technology, 2025 DOI:10.48175/IJARSCT-30412