When should audit firms introduce analyses of big data into the audit process?

Anna M. Rose, Jacob M. Rose, Kerri-Ann Sanderson, Jay C. Thibodeau

Research output: Contribution to journalArticleResearchpeer-review

25 Citations (Scopus)

Abstract

This study investigates how the timing of the consideration of Big Data visualizations affects an auditor’s evaluation of evidence and professional judgments. In addition, we examine whether the use of an intuitive processing mode, as compared to a deliberative processing mode, influences an auditor’s use and evaluation of Big Data visualizations. We conduct an experiment with 127 senior auditors from two Big 4 firms and find that auditors have difficulty recognizing patterns in Big Data visualizations when viewed before more traditional audit evidence. Our findings also indicate that auditors who view Big Data visualizations containing patterns that are contrary to management assertions after they view traditional audit evidence have greater concerns about potential misstatements and increase budgeted hours more. Overall, our results suggest that Big Data visualizations used as evidential matter have fewer benefits when they are viewed before auditors examine more traditional audit evidence.

Original languageEnglish
Pages (from-to)81-99
Number of pages19
JournalThe Journal of Information Systems
Volume31
Issue number3
DOIs
Publication statusPublished - 2017
Externally publishedYes

Keywords

  • Big data
  • Deliberative processing
  • Intuitive processing
  • Pattern recognition
  • Visualizations

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