Design and evaluation of an advanced continuous data level auditing system: A three-layer structure

Kyunghee Yoon, Yue Liu, Tiffany Chiu and Miklos A. Vasarhelyi

International Journal of Accounting Information Systems, 2021, vol. 42, issue C

Abstract: Audit efficiency and effectiveness can be significantly affected by data aggregation during audit procedures. Previous studies highlight that an appropriate level of data aggregation is needed because a continuous auditing (CA) system often generates numerous alarms. To respond to this issue, this study proposes a CA system with a three-layer structure. In the first layer of the proposed system, all journal entry level transactions are classified and aggregated using defined rules; any transactions that deviate from these rules are identified as unusual transactions. The second layer detects the observations that violate controls. Analytical monitoring models are developed in the final layer to identify observations that statistically deviate from an organization’s typical business behaviors. To examine whether the proposed three-layer CA system enhances the effectiveness of a CA systemin identifyingfinancial irregularities,this studyempirically tests the proposed models using real-world journal entry data from a construction company. The results indicate that the proposed framework enhances audit effectiveness and efficiency.

Keywords: Continuous auditing; Analytical procedure (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ijoais:v:42:y:2021:i:c:s1467089521000269

DOI: 10.1016/j.accinf.2021.100524

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