Machine Learning Innovations in Credit Card Approval: A Comparative Study of Algorithms

Aman P Joy, Reshma R Bhat, Vidya Rao

2025

Abstract

In the ever-changing financial services industry, credit card approval is increasingly reliant on innovative creditworthiness assessment algorithms. Traditional evaluation techniques, which examine applicants’ demographic and financial information, are no longer adequate because of the amount and complexity of information accessible. By using machine learning (ML) models—specifically, logistic regression, random forests, decision trees, and support vector machines—to increase predictive accuracy over traditional credit scoring systems, this study seeks to improve the credit card acceptance process. By employing accurate experimental methodologies, the efficiency of these models is compared to traditional credit scoring techniques, revealing significant enhancements in credit card approval precision, reducing errors and improving fraud detection capabilities, especially in developing countries. This study provides significant insights for financial organizations looking to improve their methods for managing credit risk and address issues such as integrity, interpretation, and dynamic risk evaluation in credit card acceptance processes.

Paper Citation

in Harvard Style

P Joy A., R Bhat R. and Rao V. (2025). Machine Learning Innovations in Credit Card Approval: A Comparative Study of Algorithms. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 592-599. DOI: 10.5220/0013582200004664

in Bibtex Style

@conference{incoft25,
author={Aman P Joy and Reshma R Bhat and Vidya Rao},
title={Machine Learning Innovations in Credit Card Approval: A Comparative Study of Algorithms},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={592-599},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013582200004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Machine Learning Innovations in Credit Card Approval: A Comparative Study of Algorithms
SN - 978-989-758-763-4
AU - P Joy A.
AU - R Bhat R.
AU - Rao V.
PY - 2025
SP - 592
EP - 599
DO - 10.5220/0013582200004664
PB - SciTePress