REAL-TIME FRAUD DETECTION: A BANKING INDUSTRY CASE STUDY
Keywords:
Real-time Fraud Detection, Machine Learning Analytics, Stream Processing Architecture, Financial Transaction Security, Digital Payment SystemsAbstract
This comprehensive article examines the implementation and evolution of real-time fraud detection systems in modern banking environments. The article explores the transformation of digital payment landscapes, focusing on the architectural frameworks, implementation strategies, and performance metrics of advanced fraud detection systems. The article demonstrates how financial institutions can effectively combat sophisticated fraud patterns while maintaining operational efficiency through detailed analysis of system components, stream processing, machine learning models, and data management strategies. The article encompasses core infrastructure components, data processing pipelines, performance achievements, operational challenges, and future improvements, providing valuable insights into best practices and lessons learned from enterprise-scale deployments.
References
PWC India, "Combating fraud in the era of digital payments," May 2022. [Online]. Available: https://www.pwc.in/assets/pdfs/consulting/financial-services/fintech/payments-transformation/combating-fraud-in-the-era-of-digital-payments.pdf
Cosive Technologies, "Fraud Detection in Banking: Q2 2024 Guide." [Online]. Available: https://www.cosive.com/fraud-detection-in-banking-guide
Abi Litty, "Real-Time Fraud Detection in Financial Transactions: Leveraging Machine Learning and Stream Processing for Dynamic Risk Assessment," in EasyChair Preprint, August 7, 2024. [Online]. Available: https://easychair.org/publications/preprint/dpvM/open
Marius Laska, Stefan Herle, Ralf Klamma, and Jörg Blankenbach, "A Scalable Architecture for Real-Time Stream Processing of Spatiotemporal IoT Stream Data—Performance Analysis on the Example of Map Matching," ISPRS Int. J. Geo-Inf. 2018, 7(7), 238, 21 June 2018. [Online]. Available: https://www.mdpi.com/2220-9964/7/7/238
Abi Litty, "Real-Time Fraud Detection in Financial Transactions: Leveraging Machine Learning and Stream Processing for Dynamic Risk Assessment," EasyChair Preprint, August 7, 2024. [Online]. Available: https://easychair.org/publications/preprint/dpvM/open
Ludivia Hernandez Aros et al., "Financial fraud detection through the application of machine learning techniques: a literature review," Humanities and Social Sciences Communications volume 11, Article number: 1130 (2024), 03 September 2024. [Online]. Available: https://www.nature.com/articles/s41599-024-03606-0
Oluwabusayo Adijat Bello et al., "Analysing the Impact of Advanced Analytics on Fraud Detection: A Machine Learning Perspective," European Journal of Computer Science and Information Technology, 11 (6),103-126, 2023. [Online]. Available: https://eajournals.org/ejcsit/wp-content/uploads/sites/21/2024/06/Analysing-the-Impact-of-Advanced-Analytics.pdf
Amruta Dhole et al., "A Quantitative Analysis to Estimate Transaction Fraud using Machine Learning," International Research Journal of Engineering and Technology, VOLUME: 08 ISSUE: 12 | DEC 2021. [Online]. Available: https://www.irjet.net/archives/V8/i12/IRJET-V8I1270.pdf
Mustafa Mohamed Ismail and Mohd Anul Haq, "Enhancing Enterprise Financial Fraud Detection Using Machine Learning," Engineering, Technology & Applied Science Research, Vol. 14 No. 4 (2024): August, 2024. [Online]. Available: https://etasr.com/index.php/ETASR/article/view/7437
Julien Haye, "How to Integrate Fraud Detection and Prevention into Your Enterprise Risk Management Framework," Aevitium, Jun
[Online]. Available: https://www.aevitium.com/post/how-to-integrate-fraud-detection-and-prevention-into-your-enterprise-risk-management-framework
Surendra Mohan Devaraj, "Next-Generation Fraud Detection: A Technical Analysis of AI Implementation in Financial Services Security," International Journal for Multidisciplinary Research (IJFMR), Volume 6, Issue 6, November-December 2024. [Online]. Available: https://www.ijfmr.com/papers/2024/6/31012.pdf
Waleed Hilal, S. Andrew Gadsden, John Yawney, "Financial Fraud: A Review of Anomaly Detection Techniques and Recent Advances," Expert Systems with Applications, Volume 193, 1 May 2022, 116429. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0957417421017164
