Risk-Based Internal Audit in the Digital Era: Trends, Implications, and Challenges

Abstract

This study examines risk-based internal audit (RBIA) in the context of digitalization, implications and future challenges. Technologies such as big data analytics, artificial intelligence (AI) and blockchain can improve operational efficiency but also create new, more complex risks such as cybersecurity, data misuse and technology-based fraud. This study uses qualitative research methods with a literature review approach to identify, evaluate and synthesize literature on risk-based internal audit, including journal articles, papers and other academic documents about digital trends, their implications and challenges. This study shows that risk-based internal audit (RBIA) has moved from periodic, sample-based inspections to a continuous, data-driven audit process that is integrated with the organization's risk management. Audit procedures become faster and easier with digital RBIA. Technological issues, human resource competencies, cultural resistance to change, regulatory components and standards, and cross-functional collaboration