AI-Driven Cybersecurity Governance Framework for Securing Digital Financial and Asset Ecosystems

This preprint proposes an AI-driven cybersecurity governance framework designed to strengthen the security, operational resilience, and governance integrity of modern digital financial and asset ecosystems. As financial infrastructures increasingly depend on cloud-native systems, artificial intelligence, fintech platforms, digital assets, and interconnected digital services, traditional cybersecurity models face growing limitations in addressing adaptive and evolving cyber threats. The study explores how governance-oriented cybersecurity architectures can improve operational trust, cyber resilience, threat intelligence integration, and adaptive risk management across digital financial ecosystems. The proposed framework integrates AI-driven threat detection, behavioural anomaly analysis, governance-based policy orchestration, contextual risk scoring, and continuous verification mechanisms into a unified cybersecurity governance architecture. A mixed-method research design is adopted, combining quantitative cybersecurity analysis using benchmark intrusion detection datasets with qualitative governance and operational resilience evaluation aligned with modern cybersecurity governance principles, Zero Trust Architecture, and financial digital resilience requirements. The paper contributes to cybersecurity governance research by bridging technical cybersecurity operations with governance-driven resilience management for digital financial ecosystems, fintech infrastructures, digital asset environments, and future AI-enabled financial systems. Keywords: AI-Driven Cybersecurity, Cybersecurity Governance, Financial Cyber Resilience, Digital Asset Security, Operational Trust, FinTech Security, Zero Trust Architecture, AI Governance.