Continuous Auditing in Big Data Computing Environments: Towards an Integrated Audit Approach by Using CAATTs

نویسندگان

  • Andreas Kiesow
  • Novica Zarvic
  • Oliver Thomas
چکیده

Through the risen operating of autonomous and automated Accounting Information System (AIS), enterprises are increasingly faced with the growing size of accounting-relevant data. Therefore, the audit’s purpose, which is namely to examine the true and fair view of financial statements, is heavily increasing in complexity. To cover the requirements to AIS in Big Data Computing Environments, we strive for the development of a Continuous Auditing (CA) approach. Since, the implementation of CA is a recognized challenge among researchers and practitioners, and traditional audit tools and techniques neglect the potential of Big Data Analytics, we strive for the development of appropriate computer-assisted audit tools and techniques (CAATTs). Therefore, we analyzed established CAATTs considering the dimensions of the Big Data paradigm in this paper. To do so, we analyzed relevant literature and viewpoints of occupational organizations. This led us to a first proposal of a conceptual architecture for the integrated audit approach. We conclude this paper with a critical discussion and emphasize implications for further work.

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تاریخ انتشار 2014