Internal Auditing Functions and Their Role in Corporate Governance Systems

Abstract

This research presents a novel, cross-disciplinary framework for conceptualizing the internal auditing function, moving beyond its traditional compliance and
financial oversight role to position it as the central nervous system of an organization’s corporate governance. Departing from conventional audit methodologies,
we propose a bio-inspired, adaptive systems model that draws principles from computational neuroscience, complex adaptive systems theory, and organizational cybernetics. The core innovation lies in reframing internal audit not as a periodic
control check, but as a continuous, intelligent sensing and regulatory mechanism
embedded within the governance architecture. We formulate and investigate three
primary research questions: (1) How can principles of homeostasis and allostasis
from biological systems be operationalized to create a self-regulating, anticipatory
internal audit process? (2) What is the efficacy of a neural network-inspired audit
risk assessment model that learns and adapts from organizational ’signals’ versus static, checklist-based approaches? (3) Can a simulated, agent-based model of
governance interactions demonstrate that an integrated, systemic audit function
improves resilience to emergent risks? Our methodology employs a hybrid design,
combining the development of a theoretical adaptive audit framework with computational simulation using agent-based modeling to test its dynamics. The results
from the simulation experiments indicate that the proposed systemic audit model
significantly enhances the detection of non-linear, emergent risks—such as cultural
degradation and strategic misalignment—which are often opaque to traditional audits. Furthermore, the model demonstrates improved organizational adaptation
speed to external shocks by reducing ’governance latency.’ The conclusion asserts
that the most significant contribution of this work is the paradigmatic shift it advocates: internal auditing must evolve from a rear-view mirror function to a forwardlooking, integrative governance sensor, fundamentally altering its design principles
and value proposition. This research opens a new avenue for audit science, one
grounded in the theories of complex systems and biological regulation, with profound implications for how governance structures are engineered in an increasingly
volatile world