The Relationship Between Internal Audit Effectiveness and Organizational Risk Governance Frameworks

Posted: Apr 06, 2023

• Bennett Carter
• Isabella Hunt
• Bryce Ford

Abstract

This research investigates the complex interplay between internal audit effectiveness and organizational risk governance frameworks through a novel computational modeling approach that integrates agent-based simulation with network analysis. Traditional studies in this domain have predominantly relied on survey-based methodologies and case studies, limiting their ability to capture the dynamic, multi-level interactions that characterize modern organizational risk environments. Our study introduces a computational framework that models organizations as complex adaptive systems, where internal audit functions and risk governance mechanisms co-evolve through iterative interactions. We developed a sophisticated simulation environment incorporating 1,500 virtual organizations with varying governance structures, audit capabilities, and risk profiles. The model incorporates three innovative dimensions: quantum-inspired uncertainty modeling for risk assessment, neuromorphic learning algorithms for audit adaptation, and bio-inspired optimization for governance structure evolution. Our findings reveal several counterintuitive relationships, including non-linear threshold effects where marginal improvements in audit quality produce disproportionate governance benefits beyond certain critical points. We also identify emergent patterns of risk contagion that traditional linear models fail to capture, demonstrating how weak governance nodes can compromise otherwise robust systems through network effects. The research contributes both methodologically through its computational approach and substantively through its identification of previously unrecognized dynamics in audit-governance relationships. These insights have significant implications for designing more resilient organizational structures in an increasingly complex risk landscape.