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Research Paper | Computer Science and Information Technology | United States of America | Volume 12 Issue 12, December 2023 | Popularity: 5.2 / 10
AI-Based Fake Transaction Detection in Credit Card Payments
Omkar Reddy Polu
Abstract: With an exponential rise in online transactions there has also been a significant increase in fraudulent activities calls for such robust means of online credit card fraud detection with real time capabilities. However, traditional rule- based fraud detection systems are slow to change in face of new evolving fraudulent patterns, thus it is not an efficient method for sophisticated adversarial attack. In this research, an AI based framework, integrating the deep learning and explainable AI (XAI) for fraud detection model is proposed which will improve the transparency and adaptability of fraud detection models. To identify fraudulent transactions, the proposed approach uses a set of transformer-based neural networks and graph based anomaly detector as an ensemble. In addition, we include federated learning to carry on decentralized, privacy preserving fraud detection amongst financial institutions without conveying delicate customer data. Adversarial training on the model makes it continuously more resilient to the emergent attack vectors. Results of that study are shown to be superior than state - of - the - art fraud detection systems on real world financial datasets, having very low false positives whilst maintaining high recall. The finding stresses on the fact that an interpretable AI needs to be integrated with scalable fraud detection techniques to strengthen financial security against emerging cyber threats. This proposed paradigm based on AI - driven paradigm is a game changer for real time secure credit card transaction monitoring.
Keywords: Credit Card Fraud Detection, Explainable AI, Transformer Networks, Federated Learning, Adversarial Training
Edition: Volume 12 Issue 12, December 2023
Pages: 2205 - 2210
DOI: https://www.doi.org/10.21275/SR23126171341
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