AI-Powered Cybersecurity Mesh for Financial Transactions: A Generative-Intelligence Paradigm for Payment Security ^†

The rapid expansion of digital payment channels has significantly widened the financial transaction attack surface, exposing ecosystems to sophisticated, polymorphic threat vectors. This study introduces an AI-powered cybersecurity mesh that unites Generative AI (GenAI), federated reinforcement learning, and zero-trust principles, with a forward-looking architecture designed for post-quantum readiness. The architecture ingests high-velocity telemetry, coordinates self-evolving agent collectives, and anchors model provenance in a permissioned blockchain to guarantee verifiability and non-repudiation. Empirical evaluations across two production-scale environments—a mobile wallet processing two million transactions per day and a high-throughput cross-border remittance rail—demonstrate a 95.1% threat-detection rate, a 62% reduction in false positives, and a 35.7% latency decrease compared to baseline systems. These results affirm the feasibility of a generative cybersecurity mesh as a scalable, future-proofed blueprint for next-generation payment security.