AI-Powered Fraud Detection in Financial Services: A Scalable Cloud-Based Approach
Keywords:
AI-powered fraud detection, machine learningAbstract
Fraud detection using AI in financial services has emerged as a crucial component in reducing the evolved cyber threats and ensures transaction security. The purpose of this research paper is to examine the integration of machine learning and AI driven anomaly detection models in cloud-based infrastructure which can enhance fraud detection in fintech services. By using frameworks like Apache Flink and Apache Kafka which is used for real- time streaming process will help in exploring scalable fraud detection architectures which enables high-throughput, low-latency processing of financial transactions.
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References
M. S. L. Zhang, L. Chen, and H. Zhan, "A Survey of Machine Learning in Financial
Fraud Detection," IEEE Access, vol. 7, pp. 64838-64850, 2019.
J. Zhang, Z. Li, and Y. Zhang, "Fraud Detection Using Machine Learning: A Survey,"
IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 8, pp.
-2270, 2019.
Singu, Santosh Kumar. "Real-Time Data Integration: Tools, Techniques, and Best
Practices." ESP Journal of Engineering & Technology Advancements 1.1 (2021):
-172.
Singu, Santosh Kumar. "ETL Process Automation: Tools and Techniques." ESP
Journal of Engineering & Technology Advancements 2.1 (2022): 74-85.
L. J. Yang, H. T. Chiu, and P. F. Hsu, "Data Stream Mining for Fraud Detection in
Financial Transactions," IEEE Transactions on Knowledge and Data Engineering,
vol. 27, no. 6, pp. 1569-1582, 2015.
H. K. Goh, P. Liu, and W. H. Cheng, "Cloud Computing and Big Data: A Perfect
Match for Financial Fraud Detection," IEEE Cloud Computing, vol. 4, no. 1, pp. 44-
, 2017.
J. A. D. Lee, "AI-Based Fraud Detection for Financial Services," IEEE Transactions
on Artificial Intelligence, vol. 10, no. 3, pp. 234-245, 2021.
A. Gupta and A. Sharma, "Anomaly Detection for Fraud Prevention: A Machine
Learning Approach," IEEE Transactions on Computational Intelligence, vol. 12, no. 4,
pp. 1441-1452, 2020.
G. S. Syed, F. A. Khan, and S. M. A. Rizvi, "AI-Based Fraud Detection: An Overview
of Machine Learning Techniques," IEEE Access, vol. 8, pp. 2302-2317, 2020.
Y. Wang, J. Xu, and L. Zhang, "Predicting Financial Fraud Using Deep Learning
Algorithms," IEEE Transactions on Cybernetics, vol. 49, no. 9, pp. 3482-3491, 2019.
M. K. Das, "Big Data and Cloud Computing for Fraud Detection in Financial
Transactions," IEEE Transactions on Services Computing, vol. 12, no. 3, pp. 405-
, 2019.
B. R. Menon, A. Kumar, and S. P. Singh, "Real-Time Stream Processing with Apache
Kafka for Fraud Detection Systems," IEEE Transactions on Cloud Computing, vol. 8,
no. 5, pp. 1407-1417, 2020.
M. L. Besson, "Apache Flink for Real-Time Fraud Detection," Proceedings of the
IEEE International Conference on Data Engineering, pp. 221-230, 2019.
R. Gupta, N. Y. Lee, and S. Pandey, "Application of Machine Learning and Cloud
Computing in Financial Fraud Prevention," IEEE Cloud Computing Conference, pp.
-10, 2018.
S. L. Walters, "Scalable Machine Learning for Financial Fraud Detection in Cloud
Environments," IEEE Transactions on Cloud Computing, vol. 7, no. 4, pp. 289-299,
M. S. Ramamoorthy and J. H. Kuo, "AI in Fraud Detection for Financial Institutions:
Challenges and Opportunities," IEEE Transactions on Financial Technology, vol. 6,
no. 1, pp. 40-50, 2020.
M. S. Kumar and T. V. Kumar, "Modeling and Detecting Fraud in Financial
Transactions Using Big Data Analytics," IEEE Transactions on Knowledge and Data
Engineering, vol. 29, no. 8, pp. 1852-1863, 2017.
K. Y. Wu and Y. Q. Zhang, "Anomaly Detection with Stream Processing for Financial
Fraud Detection," IEEE Transactions on Big Data, vol. 6, no. 2, pp. 314-325, 2019.
M. T. Alharthy, M. A. Sarfraz, and T. U. Khan, "Machine Learning for Real-Time Fraud
Detection in Financial Data," IEEE Transactions on Emerging Topics in Computing,
vol. 8, no. 5, pp. 1167-1179, 2020.
X. Chen and Y. Wang, "Federated Learning for Privacy-Preserving Fraud Detection in
Financial Institutions," IEEE Transactions on Cloud Computing, vol. 9, no. 4, pp. 987-
, 2021.
Y. A. Varma and S. K. Gupta, "Stream Processing with Apache Kafka and Flink for
Real-Time Fraud Detection," IEEE International Conference on Cloud Computing
Technology and Science, pp. 401-409, 2019.
F. M. Turner, "Cloud-Based AI for Financial Fraud Detection: Future Directions and
Innovations," IEEE Transactions on Computational Intelligence, vol. 19, no. 7, pp.
-1297, 2020.
