The COVID-19 Black Swan: Auditing Uncertainty

• In Event: Continental Breakfast - RESEARCH INTERACTION FORUM
  In Roundtable Session: Research Interaction Forum

Abstract

This paper is about auditing uncertainty. The COVID-19 pandemic is an unexpected and rare outlier event with enormous and broad reaching consequences that we will probably not be able to understand and explain until after the fact – in other words, a “Black Swan” (Taleb 2007). Such a rare and unanticipated event like COVID-19 causes uncertainty for society, its businesses, and their auditors. This paper discusses how audit analytical applications need to evolve given this Black Swan event, COVID-19. The auditor’s inability in this COVID-19 environment to appropriately assess and predict business risk using traditional deterministic statistical methods, where the auditor is generally unaware or unable to differentiate what data is relevant and accurate, means that the auditor must pivot rapidly to an audit of uncertainty using prescriptive analytics, stochastic models, and Big Data. Auditing uncertainty is relevant to academics, practitioners, and regulators of the auditing profession beyond this COVID-19 event.

Authors

• Deniz A Appelbaum, Montclair State University

• Danielle Rose Lombardi, Villanova University

• Janice C. Sipior, Villanova University