Behavioral Implications of Big Data's Impact on Audit Judgment and Decision Making and Future Research Directions

Abstract

SYNOPSIS This paper addresses information processing weaknesses and limitations that can impede the effective use and analysis of Big Data in an audit environment. Drawing on the literature from psychology and auditing, we present the behavioral implications Big Data has on audit judgment by addressing the issues of information overload, information relevance, pattern recognition, and ambiguity. We also discuss the challenges that auditors encounter when incorporating Big Data in audit analyses and the various analytical tools that are currently used by companies in the analysis of Big Data. The manuscript concludes by raising questions that future research might address related to utilizing Big Data in auditing.

Exploring the conceptual structure of the auditing discipline through co‐word analysis: An international perspective

“…The consistent decline in fragmentation and increase in connectedness within the co-word network showed that the auditing discipline is becoming increasingly tight and cohesive (Kılıç et al, 2019;Varga, 2011 Advances in information technology, the rise of the real-time economy, and massive fraud scandals played a major role in the emergence of continuous auditing practices (Eulerich & Kalinichenko, 2018). Researchers have generally tended to study continuous auditing using XML-based accounting systems (Murthy & Groomer, 2004), in an internal auditing context (Gonzalez, Sharma, & Galletta, 2012), to determine whether it enhances financial reporting quality (Lee, Kang, Oh, & Pyo, 2014), to assess how to minimize the cost of continuous audit practices arising from the maintenance of a large dataset (Pathak, Chaouch, & Sriram, 2005;Pathak, Nkurunziza, & Ahmed, 2007), and to evaluate the incremental value of continuous auditing practice (Farkas & Murthy, 2014 ; the drivers of, and obstacles to, big data evolution in audits (Alles, 2015); the consequences of big data in accounting and auditing (Krahel & Titera, 2015); the impact of big data on audit evidence; and audit judgments and financial statement audits (Brown-Liburd, Issa, & Lombardi, 2015;Cao, Chychyla, & Stewart, 2015;Yoon, Hoogduin, & Zhang, 2015). It therefore seems to be a strong candidate for one of the future research avenues.…”

A multidisciplinary perspective of big data in management research

“…Especially social media has great effects on stock performance (Schniederjans et al, 2013;Yu et al, 2013). Besides, by incorporating big data, accounting nature and audit judgement are also changing (Vasarhelyi et al, 2015;Brown-Liburd et al, 2015). Textual data is effectively used to detect financial fraud in reports (Glancy and Yadav, 2011) and Cao et al (2015) discuss the potential adoption of big data analytics to improve financial statement audits efficiency.…”

Imagineering Audit 4.0

“…Although the IT audit (Audit 2.0) emerged in the 1970s, and most all businesses are currently computer based, only about 15 percent of auditors are IT enabled (Protiviti 2015). This delay of IT adoption can be partially attributed to the conservatism and rigidity of the profession, as well as the calcifying effect of increasingly obsolete regulation (Liu and Vasarhelyi 2014), but also to the lack of quality tools that would allow traditional auditors (i.e., those without IT and analytics training) to automate the functions that they currently perform manually (Brown-Liburd, Issa, and Lombardi 2015). The key characteristics of these audit generations are presented in Table 1.…”