Development of comprehensive fraud detection systems for real-time payment processing in commercial banking

Posted: Oct 28, 2025

• Dr. Lucas Silva
• Dr. Lucas Weber
• Dr. Nora Ortega

Abstract

The rapid digitization of financial services has fundamentally transformed the banking landscape, creating unprecedented opportunities for efficiency and customer convenience while simultaneously introducing sophisticated vulnerabilities to fraudulent activities. Real-time payment processing systems, which have become the backbone of modern commercial banking, present particularly challenging security requirements due to their inherent speed constraints and the irreversible nature of transactions. Traditional fraud detection methodologies, predominantly based on rule-based systems and classical machine learning approaches, increasingly demonstrate limitations in addressing the evolving sophistication of financial fraud schemes. This research addresses the critical gap in current fraud detection capabilities by proposing a fundamentally novel approach that integrates principles from quantum computing, behavioral biometrics, and privacy-preserving machine learning. The central research question investigates whether quantum-inspired computational models can enhance fraud pattern recognition beyond the capabilities of classical algorithms when applied to real-time payment processing environments. Additionally, this study explores the feasibility of continuous behavioral authentication as a complementary fraud detection modality and examines the potential of federated learning architectures to enable cross-institutional collaboration while maintaining data privacy.