Internal audit functions face increasing pressure to enhance audit quality, ensure independence, identify emerging risks, and provide value-adding assurance within complex organizational environments. Traditional audit approaches are largely manual, compliance-oriented, and transaction-focused have struggled to respond adequately to growing operational complexity, digital transformation, and risk volatility. Prior to 2018, scholars and practitioners recognized that the integration of technology-enabled risk assessment mechanisms could significantly strengthen internal audit quality by improving risk identification, enhancing analytical depth, supporting continuous monitoring, and enabling data-driven audit planning. However, the literature remained fragmented across internal auditing, risk management, information systems, and technology adoption studies. This paper synthesizes pre-2018 scholarship to propose a conceptual model that aligns internal audit quality determinants with technology-enabled risk assessment processes. The model identifies how governance structures, information quality, analytical tools, audit methodologies, and organizational capabilities interact to produce higher-quality audit outcomes. By grounding the model in established theory and regulatory principles, the paper contributes to the advancement of audit quality research and provides guidance for developing technology-supported internal audit environments.
Internal audit quality; Risk assessment; Technology-enabled auditing; Governance; Data analytics; Assurance frameworks.
IRE Journals:
Olawole Akomolafe, Michael Uzoma Agu "A Conceptual Model for Enhancing Internal Audit Quality through Technology-Enabled Risk Assessment Frameworks" Iconic Research And Engineering Journals Volume 1 Issue 9 2018 Page 458-475
IEEE:
Olawole Akomolafe, Michael Uzoma Agu
"A Conceptual Model for Enhancing Internal Audit Quality through Technology-Enabled Risk Assessment Frameworks" Iconic Research And Engineering Journals, 1(9)