Big data analytics in financial statement audits

Min Cao, Roman Chychyla, Trevor Stewart

Research output: Contribution to journalArticlepeer-review

133 Scopus citations


Big Data analytics is the process of inspecting, cleaning, transforming, and modeling Big Data to discover and communicate useful information and patterns, suggest conclusions, and support decision making. Big Data has been used for advanced analytics in many domains but hardly, if at all, by auditors. This article hypothesizes that Big Data analytics can improve the efficiency and effectiveness of financial statement audits. We explain how Big Data analytics applied in other domains might be applied in auditing. We also discuss the characteristics of Big Data analytics, which set it apart from traditional auditing, and its implications for practical implementation.

Original languageEnglish (US)
Pages (from-to)423-429
Number of pages7
JournalAccounting Horizons
Issue number2
StatePublished - Jun 2015


  • Analytical methods
  • Auditing
  • Big data

ASJC Scopus subject areas

  • Accounting


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