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.
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Brown-Liburd, Issa, and Lombardi identified the complementary risk that information overload and ambiguity in large data environments degrade rather than improve auditor judgment unless the decision environment is deliberately structured.
“Brown-Liburd, Issa, and Lombardi (2015) had earlier identified the complementary risk: information overload and ambiguity in large data environments degrade rather than improve auditor judgment unless the decision environment is deliberately structured.”
From Auditing the Black Box: Rethinking Audit Assurance and Professional Liability in the Age of Artificial Intelligence (2026) · cites this paper as Brown-Liburd, Issa, and Lombardi (2015)
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References 85 · Cited by 434
- Authors
- Brown-Liburd, H., Issa, H., & Lombardi, D.
- Affiliations
- 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.
- Rutgers, The State University of New Jersey (US)
- Venue
- Accounting Horizons
- Publisher
- American Accounting Association
- Published
- 2015-06-01
- Volume
- 29
- Issue
- 2
- Pages
- 451-468
- ISSN
- 0888-7993 (ISSN-L)
- 1558-7975
- OpenAlex
- W2150533597
- Cited by
- 434
- References
- 85
- Citations by year
- 2026: 55 · 2025: 52 · 2024: 55 · 2023: 46 · 2022: 41 · 2021: 48 · 2020: 39 · 2019: 30 · 2018: 25 · 2017: 23 · 2016: 13 · 2015: 6
- FWCI
- 97.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Accounting Horizons (publishedVersion)
- Rutgers University Community Repository (Rutgers University) (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Accounting › Auditing, Earnings Management, Governance
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- big data, auditor judgment, auditor decision-making, information overload, information relevance, pattern recognition, ambiguity, behavioral biases, information processing limitations, big data analytics tools
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