Evaluating the Role of Internal Audit in Enhancing Risk Management in Multinational Organizations

Posted: Apr 01, 2006

• Levi Kelly
• Autumn Fox
• Ember Wells

Abstract

The contemporary business landscape for multinational organizations is characterized by unprecedented complexity, regulatory diversity, and interconnected risk exposures. Traditional approaches to understanding the relationship between internal audit functions and risk management systems have predominantly relied on qualitative assessments, case studies, and compliance-based evaluations. This research introduces a paradigm shift by developing and applying computational methodologies to quantitatively analyze this critical organizational relationship. The novelty of our approach lies in the integration of network science, machine learning, and dynamic systems modeling to create a comprehensive framework for evaluating audit effectiveness in risk mitigation. Multinational corporations operate across multiple jurisdictions with varying regulatory requirements, cultural contexts, and risk profiles. The internal audit function in such organizations has evolved from a primarily compliance-oriented activity to a strategic partner in enterprise risk management. However, the precise mechanisms through which internal audit activities translate into enhanced risk management outcomes remain inadequately understood through conventional research methods. Our research addresses this gap by proposing a computational framework that models the audit-risk relationship as a dynamic, multi-layered network.