AI for Financial Fraud Detection & Prevention workshop will explore the cutting-edge artificial intelligence and machine learning approaches for combating financial fraud, addressing one of the most critical challenges that financial institutions face. Participants will gain both theoretical understanding and practical insights into AI techniques specifically tailored for fraud detection and prevention. The workshop aims to tackle financial sector complexities including managing vast, imbalanced datasets where fraud is rare, adapting to evolving threats, ensuring model interpretability for compliance, and protecting sensitive financial data privacy. The workshop will feature research, applications, and case studies from banking, fintech, payment processing, and cryptocurrency sectors demonstrating real-world AI implementation, illustrating both opportunities and challenges across different organizational and regulatory contexts.

This workshop will accept both full papers (8 pages) and short papers (4 pages) on topics including but not limited to:

Reinforcement learning (adaptive, autonomous) and agentic frameworks that enable self-evolving fraud prevention strategies

Integrating language models, computer vision, graph frameworks, and multimodal frameworks for comprehensive fraud detection across transactions and communications

Deep learning approaches (anamoly detection, graph analytics) for identifying sophisticated fraud patterns in transaction networks, financial crime, and money laundering schemes

Leveraging Generative & Adversarial Systems (GANs) for synthetic fraud data generation and developing robust defenses against AI-powered financial attacks

Advanced ensemble methods for high-speed fraud prevention in digital real-time financial payments and cryptocurrency transactions

Explainable AI and Interpretable models for regulatory compliance and federated learning approaches for privacy-preserving fraud detection

Real-world in-production applications, deployment challenges, and lessons learned in financial fraud detection and prevention systems