Data visualization and cognitive biases in audits
ISSN: 0268-6902
Article publication date: 13 August 2019
Issue publication date: 9 April 2021
Abstract
Purpose
This paper aims to examine major cognitive biases in auditors’ analyses involving visualization, as well as proposes practical approaches to address such biases in data visualization.
Design/methodology/approach
Using the professional judgment framework of KPMG (2011), this study performs an analysis of whether and how five major types of cognitive biases (framing, availability, overconfidence, anchoring and confirmation) may occur in an auditor’s data visualization and how such biases potentially compromise audit quality.
Findings
The analysis suggests that data visualization can trigger and/or aggravate the common cognitive biases in audit. If not properly addressed, such biases may adversely affect auditors' judgment and decision-making.
Practical implications
To ensure that data visualization improves audit efficiency and effectiveness, it is essential that auditors are aware of and successfully address cognitive biases in data visualization. Six practical approaches to debias cognitive biases in auditors’ visualization are proposed: using data visualization to complement rather than supplement traditional audit evidence; positioning data visualization to support rather than replace sophisticated analytics tools; using a dashboard with multiple dimensions; using both visualized and tabular data in analyses; assigning experienced audit staff; and providing pre-audit tutorials on cognitive bias and visualization.
Originality/value
The study raises awareness of psychological issues in an audit setting.
Keywords
Citation
Chang, C.J. and Luo, Y. (2021), "Data visualization and cognitive biases in audits", Managerial Auditing Journal, Vol. 36 No. 1, pp. 1-16. https://doi.org/10.1108/MAJ-08-2017-1637
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited