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

Barr-Pulliam, Dereck
Brown-Liburd, Helen
Sanderson, Kerri-Ann
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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 they can provide relative to the fair presentation of the financial statements. 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) are signals of audit quality that affect jurors’ perceptions of auditor negligence after an audit failure. We predict and find that jurors’ perceptions of auditors’ personal control over the audit failure influence their assessment of negligence. We also 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. Lastly, we find that when auditors issue an adverse ICFR opinion, jurors attribute less blame to auditors and correspondingly more blame to management and the investor for an audit failure. Our study informs regulators, practitioners, and academics about the contextual effects of the ICFR opinion as well as the perceived assurance and potential litigation effects of using advanced technological tools in the audit.
auditor liability, audit data analytics, audit quality, culpable control model, internal controls
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