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Title: Big Data Analytics and the social relevance of auditing : an exploratory study
Author: Salijeni, George
ISNI:       0000 0004 7658 4081
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2019
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Big Four and mid-tier audit firms have made huge investments in developing and acquiring tools that are used to exploit Big Data (BD) environments. Further, audit regulatory agencies are also interested in understanding how audits in such environments are being conducted and the effects of these tools. Therefore, this thesis situates the deployment of tools to extract BD, referred to as Big Data Analytics (BDA) and their significance for the conduct of external audits. . It addresses two important areas, namely the promotion of BDA in the audit field and its embedding in the audit process. The promotion of BDA in the audit field is understood through the construct of rhetorical strategies, whereas the embedding of BDA in the audit process is explored using the constructs of identity regulation and affordance. These constructs are drawn from new institutional theory and the sociomateriality perspective with the objective of understanding how BDA, as audit technology, is implicated in the social relevance of auditing. The evidence is collected from 27 semi-structured interviews with individuals dealing with BDA in the audit field and beyond, from publicly available textual data from audit firms and from observations of audit firms' proprietary BDA tools. The findings indicate that, in promoting BDA, audit firms are using various discursive strategies either to stimulate more public trust in auditors' commitment to audit quality or to add value to their clients. In this regard, audit firms use teleological, ontological, historical and value-based arguments to show that BDA addresses concerns associated with audit quality. On the other hand, audit firms use cosmological arguments and arguments based on value added to show that BDA could enhance the operational efficiencies of their clients. However, the firms face challenges in relation to issues of data security and lack of understanding of the meaning of BD and the context in which BDA should be used in the audit. Further, to embed BDA, audit firms use discursive strategies aimed at 'winning hearts and minds' of auditors at all levels of the hierarchy within firms. This involves developing the identity of auditors as both data analysts and business advisors to the client who generate value for their firms by exploiting opportunities associated with BDA. Therefore, auditors are encouraged to show commitment to using BDA during audits through recruitment, capacity building, incentives, personal reviews and the industrialisation of BDA. Finally, BDA is implicated in the reconfiguration of data processes. Auditors argue that BDA offers affordances which enable them to achieve greater coverage in terms of operational scope and depth. Such affordances, in particular the use of visualisation tools, could have implications for their professional judgements because audit evidence can be manipulated and presented in various dimensions to clients. However, BDA constrains auditors who may not have the relevant expertise to operate some of its functionalities. The study contributes by providing early empirical accounts of the latest and most significant developments in audit technology. Further, it adds to prior literature on changes in audit technology by highlighting that such technological transformation also requires that auditors reconsider their professional identities. This leads to a revisited focus on not only what auditors do but also who they are (need to be). Finally, in studying technological changes in audit, the research illustrates the importance not only on how auditors make use of the technology but also the properties of the technology itself (its socio-material characteristics) as a significant influence on how it is embedded and used in practice.
Supervisor: Turley, William ; Samsonova - Taddei, Anna Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Big Data ; Data Analytics ; Auditors ; Social Relevance ; Audit Technologies ; Audit methodology ; Audit innovations