AI-POWERED CYBERSECURITY MESH FOR FINANCIAL NETWORKS: A REAL-WORLD DEPLOYMENT CASE STUDY

This paper presents a real-world implementation and evaluation of an AI-powered cybersecurity mesh deployed across a digital financial ecosystem.The system was designed to detect and mitigate real-time threats-including transaction fraud, data breaches, and adversarial behavior-through a federated network of AI agents embedded within payment gateways, APIs, and microservices.Leveraging transformer-based risk engines, anomaly detection pipelines, and zero-trust protocols [10][11] and controls mapped to NIST Cybersecurity Framework 2.0 (Feb 2024) and ISO/IEC 27001:2022, the mesh architecture demonstrated significant improvements in detection precision, time-to-response, and fraud mitigation rates during a 6-month deployment in a financial services platform.The case study highlights both the technical underpinnings and operational learnings from applying generative AI and distributed threat intelligence to safeguard financial networks at scale.