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

Author:

Brown-Liburd Helen1,Issa Hussein1,Lombardi Danielle1

Affiliation:

1. Helen Brown-Liburd is an Assistant Professor at Rutgers, The State University of New Jersey, Newark, Hussein Issa is an Assistant Professor at Rutgers, The State University of New Jersey, New Brunswick, and Danielle Lombardi is an Assistant Professor at Villanova University.

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.

Publisher

American Accounting Association

Subject

Accounting

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3. Alles, M. 2013. Developing a Framework for the Role of Big Data in Auditing: A Synthesis of the Literature. Working paper, Rutgers, The State University of New Jersey.

4. Alles, M. 2014. Drivers of the Adoption and Facilitators of the Evolution of Big Data by the Audit Profession. Working paper, Rutgers, The State University of New Jersey.

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