Purpose- This paper aims to analyze the role and effects of big data analytics on internal audit. To achieve this aim, we try to define the big data analytics and its impact on internal audit. As a course of nature of the internal audit, analytical review procedures are embedded in internal control models and fraud detection techniques. Since big data merge massive amounts of a diverse type of information with various kind of analytical tools, we also try to determine what big data analytics offer to the development of internal audit function.
Methodology- The research design is exploratory research based on a focus group to generate knowledge from different perspectives. We benefit group interaction and try to discover how internal auditors view big data and its effects on the internal audit. We also investigate the ways of implementation the big data analytics in the organization, such as hiring new analytically trained professionals or using the services of third-party solutions providers for big data.
Findings- We find similar results with the literature that big data analytics increase the effectiveness of internal audit. Using analytics in internal control, risk management and fraud detection have many benefits in identifying anomalies and exceptions and focusing more on correlation and causation.
Conclusion- Internal auditors are mostly aware of the importance of big data analytics, the different policies and methods of its implementation into the organization and its role in transforming internal audit function.