Integrating data analytics into the auditing curriculum: Insights and perceptions from early-career auditors

Abstract

This study aims to help audit educators determine how, where, and to what extent audit data analytics (ADA) should be integrated into existing auditing curriculum to better prepare students for the auditing profession. We interview early-career auditors to understand their experience with ADA and add their perspective to the literature on audit curriculum changes. This group performs many of the tasks where ADA techniques would be applied and can provide valuable insight to audit educators based on their work experience and recent completion of auditing and/or data analytics courses. Responses indicate that early-career auditors rely more routinely on traditional ADA tools (e.g., Excel) and that the use of advanced ADA tools (e.g., Power BI and Alteryx) is relatively limited. Furthermore, firm-provided training on advanced ADA tools focuses on navigating tools rather than interpretation of ADA output. We also find that, regardless of the ADA tool used, the skillset used most frequently is interpretation of ADA output to identify anomalies and determine the impact on audit testing, which could be emphasized in existing audit courses. Most participants expressed that rather than removing content from the audit course to make room for data analytics, faculty should integrate ADA within existing content, encouraging audit educators to change how they teach, rather than what they teach. Specifically, faculty can provide hands-on examples of ADA to supplement lectures on existing topics or assign case studies that use ADA tools. These findings have implications for immediate changes to integrate ADA into auditing courses that are more manageable than a complete overhaul of the audit curriculum.