Quantifying Systemic Cyber Risk in Federal Reserve-Regulated Banking Systems: An Enterprise Risk Analytics Framework Based on Zero Trust Architecture and Threat Intelligence Integration

• Asher Noah

  covenant University

  Author

The increasing sophistication of cyber threats poses a material risk to the stability of the U.S. financial system, yet existing risk management frameworks in Federal Reserve-regulated banking institutions remain largely reactive, control-gap oriented, and incapable of quantifying systemic cyber risk in financial terms. This study addresses the critical gap between technical cybersecurity operations and enterprise risk management by proposing and validating an enterprise risk analytics framework that integrates Zero Trust Architecture principles with Cyber Threat Intelligence (CTI) through the Factor Analysis of Information Risk (FAIR) economic model. Using a quantitative, design-based research methodology, the framework was validated through retrospective analysis of the 2017 Equifax breach and prospective simulation across three banking organizational profiles. The integrated framework achieved an 89.4% accuracy in predicting loss event frequencies compared to historical outcomes and demonstrated a 73% improvement in risk communication efficiency between technical and business stakeholders. Key predictors of systemic cyber risk were identified as third-party service provider concentration, identity and access management maturity, and threat actor capability indices. The framework provides regulators and banking institutions with a transparent, traceable, and reproducible methodology for quantifying cyber risk in monetary terms, enabling data-driven capital allocation and strategic investment decisions aligned with the Federal Reserve's safety and soundness mandate.

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