A Dual-Path Generative Framework for Zero-Day Fraud Detection in Banking Systems

Computer Science > Artificial Intelligence [Submitted on 17 Feb 2026] A Dual-Path Generative Framework for Zero-Day Fraud Detection in Banking Systems Nasim Abdirahman Ismail, Enis Karaarslan High-frequency banking environments face a critical trade-off between low-latency fraud detection and the regulatory explainability demanded by GDPR. Traditional rule-based and discriminative models struggle with "zero-day" attacks due to extreme class imbalance and the lack of historical precedents. This paper proposes a Dual-Path Generative Framework that decouples real-time anomaly detection from offline adversarial training. The architecture employs a Variational Autoencoder (VAE) to establish a legitimate transaction manifold based on reconstruction error, ensuring <50ms inference latency. In parallel, an asynchronous Wasserstein GAN with Gradient Penalty (WGAN-GP) synthesizes high-entropy fraudulent scenarios to stress-test the detection boundaries. Crucially, to address the non-differentiability of discrete banking data (e.g., Merchant Category Codes), we integrate a Gumbel-Softmax estimator. Furthermore, we introduce a trigger-based explainability mechanism where SHAP (Shapley Additive Explanations) is activated only for high-uncertainty transactions, reconciling the computational cost of XAI with real-time throughput requirements. Subjects: Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR) MSC classes: 68T07 ACM classes: I.2.6; K.6.5; J.1 Cite as: arXiv:2603.13237 [cs.AI]   (or arXiv:2603.13237v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2603.13237 Focus to learn more Submission history From: Enis Karaarslan Dr. [view email] [v1] Tue, 17 Feb 2026 10:20:40 UTC (136 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.CR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)