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Audit data analytics of unregulated voluntary disclosures and auditing expectations gap

  • Amir Michael
  • Rob DixonEmail author
Original Article

Abstract

The study is concerned with the usefulness of using audit data analytics of unregulated voluntary disclosures in reducing the auditing expectations gap. It argues that the lack of credibility and assurance of the unstructured voluntary disclosures and other big data will impact the level of public users’ expectations towards the quality of these unregulated voluntary disclosures. Therefore, we argue that non-financial, as well as financial data require assurance by an independent auditor. Consequently, this would expand the auditors’ role and responsibilities which will lead to raising the degree of stakeholders’ satisfaction and approaching their expectations potentially reducing the auditing expectations gap. Auditors will need to rely more heavily on big data analytics and technological techniques to perform this new role efficiently and effectively. Therefore, we provide empirical evidence that the perceptions of auditors, bankers, investors and academics, support the use of audit data analytics when providing assurance of unregulated voluntary disclosures in reducing auditing expectations gap. To do so, we categorized unregulated voluntary into eight different categories that auditing data analytics is required to capture from various sources and analyse in an informative and useful fashion.

Keywords

Auditing data analytics (ADA) Unregulated voluntary disclosures (UVD) Auditing expectations gap (AEG) Unregulated voluntary disclosures assurance (UVDA) Stakeholders–agency theory Environmental disclosures Corporate governance Mann–Whitney U nonparametric test Risk management disclosures 

Notes

Acknowledgements

The authors would like to thank the participants of the 41st World Continuous Auditing and Reporting Symposium Universidad de Huelva Spain 9–10 November 2017 for their valuable and constructive comments on the paper.

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Copyright information

© Springer Nature Limited 2019

Authors and Affiliations

  1. 1.Durham University Business SchoolDurham UniversityDurhamUK

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