Exploring perceptions of data analytics in the internal audit function

ABSTRACT

The objective of our study is to understand the use of data analytics within the internal audit function (IAF) and to investigate the types of tools internal auditors use, given the large amounts of data available to them for analytic purposes. We interview the Chief Audit Executive (CAE) in six for-profit and six not-for-profit organizations across several industries, including manufacturing, government services, energy, banking, and higher education. Our intent was to gather descriptive information with respect to the IAF, as well as quantifiable responses to specific questions about the role of data analytics in each CAE’s IAF. Our findings indicate that CAEs value professional certifications and the use of data analytics in the IAF. CAEs report that they employ data analytics at different times and for different purposes and that they are dedicating a considerable amount of the IAF budget in support of data analytics. Our findings should be of interest to CAEs as they consider various possible tools and training to support data analytics within their organisations and to academics who wish to include data analytics courses or topics in the accounting and information systems curricula to prepare students for the workplace.

KEYWORDS:

• Big data
• data analytics
• chief audit executives
• internal audit function
• interviews

Acknowledgements

The authors are grateful for the important insights and contributions offered by the Chief Audit Executives in the companies and organisations who participated in our study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Hereafter, big data, which refers to exceptionally large stores of data within an organization.

2. Although the study was conducted in the U.S., the globalization of business suggests that this topic is of interest to organizations outside of the U.S., as well.

3. Co-authors received approval from their respective Institutional Review Boards for this study.

4. Although this type of study can provide valuable insights, it does not allow us to conduct rigorous statistical analysis. As noted by Bloomfield, Nelson, and Soltes (2016, 371–372),

Fieldwork often goes unreported, particularly when it is conducted as a prelude to employing another method. We think that is unfortunate … , as reporting the insights gleaned from fieldwork helps to contextualize results, potentially leading other researchers to additional insights that can move the literature forward.

5. This article was recommended by two CAEs who pilot tested our concept and questions for this study. We included both Yin (2014) and Jacka (2016) due to their similarities in methodology recommended for conversational interviews.

6. ACL and IDEA – discussed in next section under Research Question #5.

7. ACL and IDEA are the two most commonly used data extraction software products by public accounting firms.