Incorporating Big Data into an audit poses several challenges. This article establishes how Big Data analytics satisfy requirements of audit evidence, namely that it is sufficient, reliable, and relevant. The authors bring up practical challenges (such as transferring information, privacy protection, and integration with traditional audit evidence) and provide suggestions for addressing them in incorporating Big Data into audit evidence. They also suggest that Big Data can complement tradition audit evidence at every level of audit evidence: financial statement, individual account, and audit objective.
Yoon, K., L. Hoogduin, and L. Zhang. 2015. Big data as complementary audit evidence. Accounting Horizons 29 (2): 431-438.
This paper frames Big Data in the context of audit evidence, specifically looking at the requirements for something to be considered audit evidence, to provide an argument for the usefulness of Big Data to auditors. The authors address the sufficiency, reliability, and relevance of Big Data analytics; they then outline potential challenges to using Big Data for adequate audit evidence.
The authors summarize existing literature on audit evidence as it applies to Big Data. They perform no original analyses, but rather discuss the characteristics of Big Data analytics as they relate to regulations and research findings.
The authors address: