AI and Digital Twin-Enabled Zero-Touch 6G Architecture for Fraud-Resistant Financial Transaction Governance

Financial institutions are preparing to move mission-critical payment services onto 6G networks that promise sub-millisecond latency, massive connectivity, and pervasive edge intelligence. If fraud management and security governance remain confined to siloed banking backends, this shift will magnify the impact of attacks and regulatory violations rather than reduce them. This tutorial proposes an AI and digital twin-enabled zero-touch 6G architecture for fraud-resistant financial transaction governance that treats the network as an active participant in security, compliance, and auditability. We first derive governance requirements and a 6G-specific threat landscape across scenarios such as real-time retail payments, high-value cross-border transfers, and central bank digital currency transactions. We then present a standards-centric reference architecture that integrates 3GPP network slicing and management functions, ETSI ZSM closed-loop automation, NFV/MEC-based edge hosting, and zero-trust controls inspired by NIST and ISO/IEC security and privacy frameworks. Network and transaction digital twins host AI and federated-learning models for continuous risk scoring, anomaly detection, and what-if policy testing, feeding an intent-based orchestration layer that can automatically adapt slice configurations, invoke step-up authentication, or trigger forensic logging. Deployment guidelines for operators and financial institutions illustrate how to realize the architecture with existing standards toolkits, while an open challenges section identifies research needs in financial intent standardization, unified telemetry models, privacy-preserving collaboration, and certification-ready 6G ZTN testbeds. The article thus provides a practical blueprint for secure and standardized zero-touch 6G systems in the financial domain.