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Original Article
Bank Fraud AI: ML-Based Fraud Detection in Banking Systems
Mohammed Zubair Molla1
Syeda Mahvish2
1 Student, MCA, Deccan College of Engineering and Technology, Hyderabad, Telangana, India. 2Assistant professor, MCA, Deccan College of Engineering and Technology, Hyderabad, Telangana, India.
Published Online: September-October 2025
Pages: 73-78
Cite this article
↗ https://www.doi.org/10.59256/ijire.20250605012
References
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2. A. Jurgovsky et al., “Sequence Classification for Credit-Card Fraud Detection,” Expert Systems with Applications, vol. 100, pp. 234–245, 2018. doi: 10.1016/j.eswa.2018.01.037
3. B. Liu, M. Huang, Y. Zhu, and Y. Zhang, “A New Approach for Credit Card Fraud Detection Based on Transactions Categorization,” 2018 IEEE 4th ICCC, Chengdu, 2018, pp. 1925–1929. doi: 10.1109/CompComm.2018.8780981
4. L. Carcillo et al., “Combining Unsupervised and Supervised Learning in Credit Card Fraud Detection,” Information Sciences, vol. 557, pp. 317–331, 2021. doi: 10.1016/j.ins.2020.12.033
5. Y. Sahin and E. Duman, “Detecting Credit Card Fraud by ANN and Logistic Regression,” 2011 INISTA, Istanbul, 2011, pp. 315–319. doi: 10.1109/INISTA.2011.5946108
6. D. Jha and M. Kumar, “A Survey on Credit Card Fraud Detection Techniques,” 2019 ICCCNT, Kanpur, 2019. doi: 10.1109/ICCCNT45670.2019.8944582
7. V. B. Thennakoon et al., “Real-Time Credit Card Fraud Detection Using Machine Learning,” 2019 Confluence, Noida, 2019, pp. 488–493. doi: 10.1109/CONFLUENCE.2019.8776930
8. S. Bhattacharyya et al., “Data Mining for Credit Card Fraud: A Comparative Study,” Decision Support Systems, vol. 50, no. 3, pp. 602–613, Feb. 2011. doi: 10.1016/j.dss.2010.08.008
9. R. Bolton and D. Hand, “Statistical Fraud Detection: A Review,” Statistical Science, vol. 17, no. 3, pp. 235–255, 2002. doi: 10.1214/ss/1042727940
10. X. Zhang, Q. Wang, and Y. Zhang, “A Deep Learning Approach for Fraud Detection in Credit Card Transactions,” 2020 IEEE 4th International Conference on Artificial Intelligence and Big Data, Beijing, 2020, pp. 123–128. doi: 10.1109/AIBD49058.2020.00033
2. A. Jurgovsky et al., “Sequence Classification for Credit-Card Fraud Detection,” Expert Systems with Applications, vol. 100, pp. 234–245, 2018. doi: 10.1016/j.eswa.2018.01.037
3. B. Liu, M. Huang, Y. Zhu, and Y. Zhang, “A New Approach for Credit Card Fraud Detection Based on Transactions Categorization,” 2018 IEEE 4th ICCC, Chengdu, 2018, pp. 1925–1929. doi: 10.1109/CompComm.2018.8780981
4. L. Carcillo et al., “Combining Unsupervised and Supervised Learning in Credit Card Fraud Detection,” Information Sciences, vol. 557, pp. 317–331, 2021. doi: 10.1016/j.ins.2020.12.033
5. Y. Sahin and E. Duman, “Detecting Credit Card Fraud by ANN and Logistic Regression,” 2011 INISTA, Istanbul, 2011, pp. 315–319. doi: 10.1109/INISTA.2011.5946108
6. D. Jha and M. Kumar, “A Survey on Credit Card Fraud Detection Techniques,” 2019 ICCCNT, Kanpur, 2019. doi: 10.1109/ICCCNT45670.2019.8944582
7. V. B. Thennakoon et al., “Real-Time Credit Card Fraud Detection Using Machine Learning,” 2019 Confluence, Noida, 2019, pp. 488–493. doi: 10.1109/CONFLUENCE.2019.8776930
8. S. Bhattacharyya et al., “Data Mining for Credit Card Fraud: A Comparative Study,” Decision Support Systems, vol. 50, no. 3, pp. 602–613, Feb. 2011. doi: 10.1016/j.dss.2010.08.008
9. R. Bolton and D. Hand, “Statistical Fraud Detection: A Review,” Statistical Science, vol. 17, no. 3, pp. 235–255, 2002. doi: 10.1214/ss/1042727940
10. X. Zhang, Q. Wang, and Y. Zhang, “A Deep Learning Approach for Fraud Detection in Credit Card Transactions,” 2020 IEEE 4th International Conference on Artificial Intelligence and Big Data, Beijing, 2020, pp. 123–128. doi: 10.1109/AIBD49058.2020.00033
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