The Effects of the Internal Control Opinion and Use of Audit Data Analytics on Perceptions of Audit Quality, Assurance, and Auditor Negligence

Abstract

Advanced audit data analytics tools allow auditors to analyze the entire population of accessible client transactions. Though this approach has measurable benefits for audit efficiency and effectiveness, auditors caution that it does not incrementally increase the level of assurance expressed relative to the financial statements’ fair presentation. We experimentally examine whether the audit testing methodology (audit data analytics versus traditional sampling) and the type of internal control (ICFR) opinion auditors issue (unqualified versus adverse) affect jurors’ perceptions of auditor negligence after an audit failure. We predict and find that when auditors issue an unqualified ICFR opinion, jurors make higher negligence assessments when auditors employ traditional statistical sampling techniques than when they employ audit data analytics. We also find that when auditors issue an adverse ICFR opinion, jurors attribute less blame to auditors and correspondingly more blame to the investor for an audit failure. Additional analyses reveal that jurors perceived the use of audit data analytics as an indicator of higher audit quality and are less likely to find auditors negligent. However, jurors do not perceive a difference in the level of assurance provided by the audit opinion when auditors use ADAs or traditional sampling testing methods. Our study informs regulators, practitioners, and academics about the contextual effects of the ICFR opinion and the perceived assurance and potential litigation effects of using advanced technological tools in the audit.

Keywords: auditor liability, audit data analytics, audit quality, statistical sampling

JEL Classification: M41, M42