A Study of Big Data Analytics in Internal Auditing

Neda Shabani, Arslan Munir, Saraju P. Mohanty

Research output: Chapter in Book/Report/Conference proceedingConference contribution


As the world is progressing towards an era of automation and artificial intelligence (AI), the use of data is becoming more valuable than ever before. Many professions and organizations have already incorporated automation and AI into their work to increase their productivity and efficacy. Auditing firms are not an exception in this regard as these firms are also using many data analytics processes to plan and perform audit. This paper provides a systematic review of big data analytics application in auditing with primary focus on internal auditing. The paper contemplates the advantages of incorporating big data analytics in internal auditing. The paper further discusses the state-of-the-art and contemporary trends of big data analytics in internal auditing while also summarizing the findings of notable researches in the area. Finally, the paper outlines various challenges in incorporating big data analytics in internal auditing and provides insights into future trends.

Original languageEnglish (US)
Title of host publicationIntelligent Systems and Applications - Proceedings of the 2021 Intelligent Systems Conference IntelliSys
EditorsKohei Arai
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages13
ISBN (Print)9783030821951
StatePublished - 2022
Event Intelligent Systems Conference, IntelliSys 2021 - Virtual, Online
Duration: Sep 2 2021Sep 3 2021

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


Conference Intelligent Systems Conference, IntelliSys 2021
CityVirtual, Online


  • Accounting
  • Auditing
  • Big data
  • Data analytics
  • External auditing
  • Internal auditing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications


Dive into the research topics of 'A Study of Big Data Analytics in Internal Auditing'. Together they form a unique fingerprint.

Cite this