The transformation to data analytics in Big-Four financial audit: what, why and how?
Angela Liew,
Peter Boxall and
Denny Setiawan
Pacific Accounting Review, 2022, vol. 34, issue 4, 569-584
Abstract:
Purpose - This study aims to explore the implementation of data analytics in the Big-Four accounting firms, including the extent to which a digital transformation is changing the work of financial auditors, why it is doing so and how these firms are managing the transformation process. Design/methodology/approach - The authors conducted 23 interviews with 20 participants across four hierarchical levels from three of the Big-Four accounting firms in New Zealand. Findings - The firms have entered the era of “smart audit systems”, in which auditors provide deep business insights that are communicated more effectively through data visualisation. The full potential, however, of data analytics depends not only on the transformation process within accounting firms but also on improvement in the quality of IT systems in client companies. The appointment of transformation managers, the recruitment of technology-savvy graduates and the provision of extensive training are helping to embed data analytics in the Big-Four firms. Accounting graduates in financial audit now need to show that they have the aptitude to become “citizen data scientists”. Practical implications - The findings explain how data analytics is being embraced in the Big-Four auditing firms and underline the implications for those who work in them. Originality/value - The findings challenge the “technological reluctance” thesis. In contrast, the authors observe a climate of positive attitudes towards new technology and accompanying actions in the Big-Four firms. The authors show how branches of the Big-Four firms operating distantly from their global headquarters, and with smaller economies of scale, are implementing the new technologies that characterise their global firms.
Keywords: Audit; Audit analytics; Audit revolution; Big data; Data analytics; Smart audit systems (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eme:parpps:par-06-2021-0105
DOI: 10.1108/PAR-06-2021-0105
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