Chair or Co-Chair
Dr. Jennifer Schafer
Committee Member or Co-Chair
Dr. Scott Vandervelde
Dr. Velina Popova
DATA ANALYTICS IN AN AUDIT: EXAMINING FRAUD RISK AND
This study is comprised of two papers which examine, through interviews and an experiment, the current practices of data analytics of CPA firms, whether and how fraud risk impacts the usage of data analytics in an audit, and the effect data analytics has on the efficiency and effectiveness of an audit. The implementation of data analytics in an audit is relatively new, and there is not a good understanding of how it is currently being used in practice. Although historically the auditing profession has been slow to adopt new technologies, the need for auditors to embrace new technologies is critical to keep pace with their clients. Interviews with auditors show that data analytics is used in at least half of all audits, two-thirds believe that data analytics is used more when fraud risk is high, and all of the participants stated their firm plans to increase usage of data analytics in the future.
Prior inspection reports of the Public Company Accounting Oversight Board (PCAOB) indicate auditors fail to appropriately modify their standard audit procedures in response to the risk of fraud (PCAOB, 2007, 2008). If data analytics is incorporated as a modification to standard audit procedures when fraud risk is higher, an auditor can adjust the nature and extent of the procedures and possibly provide a more efficient and effective audit. Results from the experiment show fraud risk does not influence the use of data analytics; however, a correlation exists between audit experience and a higher use of data analytics. Data analytics was shown to yield more budgeted hours; therefore, instead of being efficient from a time perspective, the use of data analytics leads to a less efficient audit. On the other hand, there is some evidence that auditors who used more data analytic procedures were less apt to perform unnecessary procedures (they were less inefficient compared to experts) and were more effective at choosing the correct procedures. Finally, there is no evidence auditors are able to effectively modify data analytic procedures in response to fraud risk, but auditors are able to modify total audit procedures as fraud increases (decreases).
Smith, Sondra, "Data Analytics in an Audit: Examining Fraud Risk and Audit Quality" (2018). Doctor of Business Administration Dissertations. 41.