REAL-TIME AI-POWERED FRAUD DETECTION: A MICROSERVICES APPROACH
Keywords:
Fraud Detection, Microservices Architecture, Machine Learning, Real-time Processing, Security Framework.Abstract
This article presents a comprehensive analysis of a real-time AI-powered fraud detection system built on microservices architecture. The system addresses the growing challenges of digital payment fraud through an innovative combination of distributed computing, machine learning, and advanced security measures. By implementing a three-tier architecture comprising data ingestion, processing, and decision layers, the system delivers robust fraud detection capabilities while maintaining high performance and scalability. The implementation leverages cutting-edge technologies including Apache Kafka for stream processing, Spring Boot microservices for distributed computing, and ensemble machine learning models for fraud detection. The article details the system's architecture, performance optimizations, security considerations, and future enhancement pathways, demonstrating how modern software engineering practices and artificial intelligence can be effectively combined to create sophisticated fraud prevention solutions.
References
I. Mettildha Mary, M. Priyadharsini, et al., "Online Transaction Fraud Detection System," IEEE, International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2021. Available: https://ieeexplore.ieee.org/document/9404750
Behshad Mohebali, Gelareh Karbaschi, et al., "An Evolutionary Framework for Real-Time Fraudulent Credit Detection," IEEE Congress on Evolutionary Computation (CEC), 2021. Available: https://ieeexplore.ieee.org/document/9504729
Dan-Alexandru Teodoras, Cosmina Stalidi, et al., "Implementing a Java Microservice for Credit Fraud Detection Using Machine Learning," IEEE 23rd RoEduNet Conference: Networking in Education and Research (RoEduNet), 2024. Available: https://ieeexplore.ieee.org/abstract/document/10722691
Rajeshwari and Sathish Babu B, "Real-time credit card fraud detection using Streaming Analytics," 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), 2016. Available: https://www.researchgate.net/publication/316530673_Real-time_credit_card_fraud_detection_using_Streaming_Analytics
Ravi Kiran Mallidi, Manmohan Sharma, et al., "Streaming Platform Implementation in Banking and Financial Systems," IEEE 2nd Asian Conference on Innovation in Technology (ASIANCON), 2022. Available: https://ieeexplore.ieee.org/abstract/document/9909500
Seyedeh Khadijeh Hashemi, et al., "Fraud Detection in Banking Data by Machine Learning Techniques," in IEEE Internet of Things Journal, vol. 10, no. 5, pp. 4136-4147, 2023. Available: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9999220
Muhammad Atif Khan Achakzai and Juan Peng, "Detecting financial statement fraud using dynamic ensemble machine learning," International Review of Financial Analysis Volume 89, October 2023, 102827. Available: https://www.sciencedirect.com/science/article/abs/pii/S1057521923003435
Chukwujekwu Damian Ikemefuna, Oluwatobiloba Okusi, et al., "Adaptive Fraud Detection Systems: Using Ml To Identify And Respond To Evolving Financial Threats," International Research Journal of Modernization in Engineering Technology and Science, vol. 6, no. 9, pp. 1727-1735, 2024. Available: https://www.irjmets.com/uploadedfiles/paper//issue_9_september_2024/61738/final/fin_irjmets1727184535.pdf
Hanae Abbassi, Berkaoui Abdellah, et al., "End-to-End Real-time Architecture for Fraud Detection in Online Digital Transactions," International Journal of Advanced Computer Science and Applications 14(6), 2023. Available: https://www.researchgate.net/publication/371970277_End-to-End_Real-time_Architecture_for_Fraud_Detection_in_Online_Digital_Transactions
Bertha Ori, Cletus Ikenna Ori, Lilian Ezekiel, "Exploring Financial Fraud Detection: A Comprehensive Analysis and Implementation of Machine Learning with Artificial Neural Network," International Journal of Advanced Research, vol. 11, no. 2, pp. 856-870, 2023. Available: https://www.researchgate.net/publication/378908863_Exploring_Financial_Fraud_Detection_A_Comprehensive_Analysis_and_Implementation_of_Machine_Learning_with_Artificial_Neural_Network
Fabrizio Carcillo, Andrea Dal Pozzolo, et al., "SCARFF: A scalable framework for streaming credit card fraud detection with spark," Information Fusion Volume 41, May 2018, Pages 182-194, 2023. Available: https://www.sciencedirect.com/science/article/abs/pii/S1566253517305444
Yeshwanth Vasa, Sukender Reddy Mallreddy "AI And Deep Learning Synergy: Enhancing Real-Time Observability And Fraud Detection In Cloud Environment, " International Journal of Research in Engineering & Management (ISSN: 2456-1029), 2023. Available: https://www.researchgate.net/profile/Yeshwanth-Vasa-2/publication/385009055_IJREM64/links/6711c04609ba2d0c7606d780/IJREM-64.pdf
Bhupendrasinh Thakre, "The Future Of Fraud Prevention: Mlops, Feature Engineering, And The Balance Of Automation And Ethics," International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 15, Issue 4, July-August, 2024. Available: https://iaeme.com/MasterAdmin/Journal_uploads/IJARET/VOLUME_15_ISSUE_4/IJARET_15_04_005.pdf
Halima Oluwabunmi Bello, Adebimpe Bolatito Ige, et al., "Adaptive machine learning models: Concepts for real-time financial fraud prevention in dynamic environments," World Journal of Advanced Engineering Technology and Sciences, 2024. Available: https://www.researchgate.net/profile/Halima-Bello-5/publication/382680355_Adaptive_machine_learning_models_Concepts_for_real-time_financial_fraud_prevention_in_dynamic_environments/links/67113a97d796f96b8ebd7220/Adaptive-machine-learning-models-Concepts-for-real-time-financial-fraud-prevention-in-dynamic-environments.pdf
Najmeddine Dhieb, Hakim Ghazzai, et al., "A Secure AI-Driven Architecture for Automated Insurance Systems: Fraud Detection and Risk Measurement," in Journal of Information Security and Applications, vol. 50, 2020. Available: https://ieeexplore.ieee.org/abstract/document/9046765
Rana, Pradumna B, "The evolving multi‑layered global financial safety net : role of Asia," S. Rajaratnam School of International Studies, University Working Paper Series, Paper No. 238, 2012. Available: https://dr.ntu.edu.sg/bitstream/10356/95321/1/WP238.pdf
Ayush Gautam, "The Evaluating the Impact of Artificial Intelligence on Risk Management and Fraud Detection in the Banking Sector," AI & IoT Review, vol. 4, no. 2, pp. 45-62, 2023. Available: https://scicadence.com/index.php/AI-IoT-REVIEW/article/view/25/25
Surendra Mohan Devaraj, "Next-Generation Fraud Detection: A Technical Analysis of AI Implementation in Financial Services Security," International Journal for Multidisciplinary Research (IJFMR), 2024. Available: https://www.ijfmr.com/papers/2024/6/31012.pdf
