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- Vol. 5 Issue 3
- Article
Decision Tree-Based Fraud Detection and Financial Data Protection in Digital Banking
Authors
1 Aditya Birla World Academy, Mumbai, Maharashtra, India.
Article Information
- DOI
- No DOI
- Published In
- Volume 5, Issue 3 (2026)
- Published Online
- September-December 2026
- Pages
- 654-657
- Article Type
- Original Article
- Check for updates
- No DOI available for cross-reference
References
1. Ali, Abdulalem, et al. “Financial Fraud Detection Based on Machine Learning: A Systematic Literature Review.” Applied Sciences, vol. 12, no. 19, 2022, article 9637. https://doi.org/10.3390/app12199637.
2. Afriyie, Jonathan Kwaku, et al. “A Supervised Machine Learning Algorithm for Detecting and Predicting Fraud in Credit Card Transactions.” Decision Analytics Journal, vol. 6, 2023, article 100163. https://doi.org/10.1016/j.dajour.2023.100163.
3. Cherif, Asma, et al. “Credit Card Fraud Detection in the Era of Disruptive Technologies: A Systematic Review.” Journal of King Saud University—Computer and Information Sciences, vol. 35, no. 1, 2023, pp. 145–174. https://doi.org/10.1016/j.jksuci.2022.11.008.
4. Hernandez Aros, Ludivia, et al. “Financial Fraud Detection through the Application of Machine Learning Techniques: A Literature Review.” Humanities and Social Sciences Communications, vol. 11, 2024, article 1130. https://doi.org/10.1057/s41599-024-03606-0.
5. Kavlakoglu, Eda. “What Is a Decision Tree?” IBM Think, https://www.ibm.com/think/topics/decision-trees.
6. Kanamori, Sachiko, et al. “Privacy-Preserving Federated Learning for Detecting Fraudulent Financial Transactions in Japanese Banks.” Journal of Information Processing, vol. 30, 2022, pp. 789–795. https://doi.org/10.2197/ipsjjip.30.789.
7. Lopez, Jude Gerald. “What Is Financial Fraud? & Its Types.” Razorpay Learn, 21 July 2025, https://razorpay.com/learn/what-is-financial-fraud/.
8. Roy, Neha Chhabra, and Sreeleakha Prabhakaran. “Internal-Led Cyber Frauds in Indian Banks: An Effective Machine Learning-Based Defense System to Fraud Detection, Prioritization and Prevention.” Aslib Journal of Information Management, vol. 75, no. 2, 2023, pp. 246–296. https://doi.org/10.1108/AJIM-11-2021-0339.
9. Wang, Shuang, et al. “Data Privacy and Cybersecurity Challenges in the Digital Transformation of the Banking Sector.” Computers & Security, vol. 147, 2024, article 104051. https://doi.org/10.1016/j.cose.2024.104051.
2. Afriyie, Jonathan Kwaku, et al. “A Supervised Machine Learning Algorithm for Detecting and Predicting Fraud in Credit Card Transactions.” Decision Analytics Journal, vol. 6, 2023, article 100163. https://doi.org/10.1016/j.dajour.2023.100163.
3. Cherif, Asma, et al. “Credit Card Fraud Detection in the Era of Disruptive Technologies: A Systematic Review.” Journal of King Saud University—Computer and Information Sciences, vol. 35, no. 1, 2023, pp. 145–174. https://doi.org/10.1016/j.jksuci.2022.11.008.
4. Hernandez Aros, Ludivia, et al. “Financial Fraud Detection through the Application of Machine Learning Techniques: A Literature Review.” Humanities and Social Sciences Communications, vol. 11, 2024, article 1130. https://doi.org/10.1057/s41599-024-03606-0.
5. Kavlakoglu, Eda. “What Is a Decision Tree?” IBM Think, https://www.ibm.com/think/topics/decision-trees.
6. Kanamori, Sachiko, et al. “Privacy-Preserving Federated Learning for Detecting Fraudulent Financial Transactions in Japanese Banks.” Journal of Information Processing, vol. 30, 2022, pp. 789–795. https://doi.org/10.2197/ipsjjip.30.789.
7. Lopez, Jude Gerald. “What Is Financial Fraud? & Its Types.” Razorpay Learn, 21 July 2025, https://razorpay.com/learn/what-is-financial-fraud/.
8. Roy, Neha Chhabra, and Sreeleakha Prabhakaran. “Internal-Led Cyber Frauds in Indian Banks: An Effective Machine Learning-Based Defense System to Fraud Detection, Prioritization and Prevention.” Aslib Journal of Information Management, vol. 75, no. 2, 2023, pp. 246–296. https://doi.org/10.1108/AJIM-11-2021-0339.
9. Wang, Shuang, et al. “Data Privacy and Cybersecurity Challenges in the Digital Transformation of the Banking Sector.” Computers & Security, vol. 147, 2024, article 104051. https://doi.org/10.1016/j.cose.2024.104051.
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