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Current Issue, Volume 18

Auditing with smart contracts
Andrea M. Rozario and Miklos A. Vasarhelyi
Published February 2018
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Blockchain-based smart contracts are emerging as a disruptive force that may change the way financial statement audits are performed and delivered. With their potential ability to autonomously execute audit procedures on behalf of the auditor and disclose the results of these audit procedures, blockchain-based smart contracts have the potential to improve audit quality and meet the information demands of various vested parties for more timely and transparent audit reporting. This paper proposes the application of smart contracts to auditing as an enabler for improved audit data analytics and close to real-time audit reporting.
 

Digital economy and corruption perceptions: A cross-country analysis
Mohammad I. Merhi and Punit Ahluwalia
Published March 2018
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The motivation of this study is the lack of empirical evidence on the ability of Information Technology related factors to reduce corruption. This paper proposes a conceptual model that depicts the relationships between macro-level technology related factors and corruption perceptions. Data are collected from reputable organizations such as EIU and Transparency International. The sample used is sixty-nine countries, making the results more generalizable than those of single case studies or smaller sample size. The hypotheses are confirmed using PLS analytical procedures and the findings are reported. We discuss the results and their implications for researchers and practitioners.
 

Embracing Textual Data Analytics in Auditing with Deep Learning
Ting Sun and Miklos A. Vasarhelyi
Published April 2018
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While the massive volume of text documents from multiple sources inside and outside of the company provides more information for auditors, the lack of efficient and effective technology solutions hampers the full use of text data. Powered by the emerging data analytics technology of deep learning, the value of the text can be better explored to deliver a higher quality of audit evidence and more relevant business insights. This research analyzes the usefulness of the information provided by various textual data in auditing and introduces deep learning, an evolving Artificial Intelligence approach. Furthermore, it provides a guide for auditors to implement deep learning techniques with pre-developed tools and open-source libraries.
 

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