Continuous audit model: data integration framework

Authors

  • Mauricio Mello Codesso Federal University of Santa Catarina (UFSC)
  • Paulo Caetano da Silva Profesor at University of Salvador (UNIFACS)
  • Miklos A. Vasarhelyi KPMG Distinguished Professor of AIS Rutgers Business School l
  • Rogério João Lunkes Professor at Federal University of Santa Catarina (UFSC)

DOI:

https://doi.org/10.5007/2175-8069.2018v15n34p144

Abstract

The approximation of business areas with the use of new technologies, real-time savings, transactions with several countries and on several continents with different law guarantees are necessary. These warranties can be acquired through Continuous Audit (CA). However, to be able to perform the analysis the auditors need to have access and extract the data. Previous researchers only emphasis on the benefits of applying the CA methods, but do not explain how to retrieve and organize the data.  The paper aims to contribute to the literature with the deepening of ways to access, structure and collect critical and necessary data for CA. With the deepening of Audit Data Standard and  XBRL, as well as creating a basis for future research with the integration of extraction, analysis, and exception detection algorithms that are used by CA.

Author Biographies

Mauricio Mello Codesso, Federal University of Santa Catarina (UFSC)

Doctor in Business Administration (UFSC), Brasil

Paulo Caetano da Silva, Profesor at University of Salvador (UNIFACS)

Pos-Doctoral at Rutgers Business School, USA

Miklos A. Vasarhelyi, KPMG Distinguished Professor of AIS Rutgers Business School l

University of California, Los Angeles, Graduate School of Management, Ph.D

Rogério João Lunkes, Professor at Federal University of Santa Catarina (UFSC)

Pos-Doctoral at Universidat de València, Spain

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Published

2018-03-28

How to Cite

Codesso, M. M., Silva, P. C. da, Vasarhelyi, M. A., & Lunkes, R. J. (2018). Continuous audit model: data integration framework. Revista Contemporânea De Contabilidade, 15(34), 144–157. https://doi.org/10.5007/2175-8069.2018v15n34p144

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Articles