BANK FRAUD AI - DETECTING FRAUD IN BANKING DATA USING MACHINE LEARNING ALGORITHM.

Authors

  • CHODAVARAPU RAJ KUMAR,Dr. S.M ROY CHOUDRI

Keywords:

Fraud Detection, Machine Learning, Artificial Intelligence, Banking Transactions, Data Imbalance, Financial Security.

Abstract

The rapid growth of digital banking and online financial transactions has increased the risk of fraudulent activities in banking systems. Fraudulent transactions cause significant financial losses and damage the reputation of financial institutions as well as customers. Therefore, early and accurate detection of fraud has become a critical requirement for modern banking systems. This paper proposes a machine learning-based approach for detecting fraudulent bank transactions effectively. Artificial Intelligence (AI) techniques are used to analyze transaction patterns and identify suspicious activities in real time

References

E. Ileberi, Y. Sun, and Z. Wang, “A machine learning based credit card fraud detection using the GA algorithm for feature selection,” Journal

of Big Data, vol. 9, no. 24, 2022.

X. Feng and S.-K. Kim, “Novel machine learning based credit card fraud detection systems,” Mathematics, vol. 12, no. 12, pp. 1–20, 2024.

J. J. Assabil, “Credit card fraud detection using machine learning algorithms: A comparative study of six models,” International Journal of

Intelligent Systems and Applications in Engineering, vol. 12, 2024.

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Published

2026-04-30

How to Cite

CHODAVARAPU RAJ KUMAR,Dr. S.M ROY CHOUDRI. (2026). BANK FRAUD AI - DETECTING FRAUD IN BANKING DATA USING MACHINE LEARNING ALGORITHM. Journal of Computational Analysis and Applications (JoCAAA), 35(4), 299–307. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5406

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Section

Articles