The human factor in the audit technology transformation

This dissertation examines audit firms’ technology-related strategies with a particular focus on the human factor. It aims to understand the challenges that emerging technologies pose to auditors’ professional skepticism and interpersonal interactions. Motivated by both practical observations and the academic literature, I experimentally examine auditors’ behavioral responses in three specific contexts: (i) the methodology of technology adoption—using inherited versus self-developed data analytics tests, (ii) the application of a specific technique—full population testing versus sample testing, and (iii) behaviors associated with technology integration—seeking advice from data analytics specialists. In Chapter 2, I demonstrate that auditors’ use of data analytics tests inherited from others, compared to developing those tests themselves, impairs their psychological ownership of the tests, thereby adversely affecting their skeptical actions. In Chapter 3, I find that auditors evaluating evidence from full population testing are subject to an attribute substitution bias, with implications for their skepticism. In Chapter 4, I find that a subordinate auditor’s prior experience seeking advice from data analytics specialists could backfire by reducing their superior’s reliance on their subsequent data analytics work. Collectively, this dissertation highlights the critical role of human factors in the effective implementation of audit technology. While audit firms’ efforts to adopt cutting-edge technology are commendable, they must also consider the unintended consequences emerging during the implementation process, particularly those related to human behavior. Addressing these behavioral challenges is crucial to maximizing the potential of audit data analytics in enhancing audit quality.