Doctor of Philosophy (PhD)
Department of Accounting
Emerging technologies have changed financial reporting. As a result, client cybersecurity risk could result in material misstatements directly related to the financial statement audit. This study estimates client cybersecurity risk using a machine learning algorithm and investigates how cybersecurity risk explains audit fees. I find that clients with higher cybersecurity risk pay higher audit fees. Moreover, auditors only charge a fee premium following a client data breach if the client has heightened cybersecurity risk. In addition, Big 4 auditors charge a smaller cybersecurity-related fee premium than non-Big 4 auditors, suggesting that Big 4 auditors are more efficient in evaluating and addressing cybersecurity-related financial risks. Finally, the auditor’s office experience of client cybersecurity events does not affect how auditors incorporate client cybersecurity risk into audit fees, indicating the auditor’s preference to keep the auditing process consistent for each client.
Jiang, Wanying, "Auditor’s Consideration of Client Cybersecurity Risk – A Machine Learning-Based Analysis" (2023). LSU Doctoral Dissertations. 6055.
Reichelt, Kenneth J.
Available for download on Thursday, February 28, 2030