Big Data and Analytics in the Modern Audit Engagement: Research Needs
Top Cited Papers
- 1 February 2017
- journal article
- Published by American Accounting Association in AUDITING: A Journal of Practice & Theory
- Vol. 36 (4), 1-27
- https://doi.org/10.2308/ajpt-51684
Abstract
Modern audit engagements often involve examination of clients that are using big data and analytics to remain competitive and relevant in today's business environment. Client systems now are integrated with the cloud, the Internet of Things, and external data sources such as social media. Furthermore, many engagement clients are now integrating this big data with new and complex business analytical approaches to generate intelligence for decision making. This scenario provides almost limitless opportunities and also the urgency for the external auditor to utilize advanced analytics. This paper first positions the need for the external audit profession to move towards big data and audit analytics. It then reviews the regulations regarding audit evidence and analytical procedures, in contrast to the emerging environment of big data and advanced analytics. In a big data environment, the audit profession has the potential to undertake more advanced predictive and prescriptive oriented analytics. The next section proposes and discusses six key research questions and ideas followed with particular emphasis on the research needs of quantification of measurement and reporting. This paper provides a synthesis and review of the concerns facing the audit community with the growing use of big data and complex analytics by their clients. It contributes to the literature by expanding upon these emerging concerns and providing opportunities for future research.Keywords
This publication has 54 references indexed in Scilit:
- Data, information and analytics as servicesDecision Support Systems, 2013
- Information Fusion in Continuous AssuranceJournal of Information Systems, 2012
- Using Nonfinancial Measures to Assess Fraud RiskJournal of Accounting Research, 2009
- Bayesian Fraud Risk Formula for Financial Statement AuditsAbacus, 2009
- Multiple hypothesis evaluation in auditingAccounting & Finance, 2002
- The belief-function approach to aggregating audit evidenceInternational Journal of Intelligent Systems, 1995
- Evidential reasoning using stochastic simulation of causal modelsArtificial Intelligence, 1987
- We Need Both Exploratory and ConfirmatoryThe American Statistician, 1980
- Subjective Probability Elicitation Techniques: A Performance ComparisonJournal of Accounting Research, 1978
- Subjective Probability Elicitation: The Effect of Congruity of Datum and Response Mode on PerformanceJournal of Accounting Research, 1977