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Big Data Analytics and Audit Quality: Evidence from Canada

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Digital Economy, Business Analytics, and Big Data Analytics Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1010))

Abstract

This paper aims to understand better how Big Data and Big Data Analytics (BDA) affect professional judgement, audit performance and perceived audit quality in Canadian audit firms. Our findings are based on semi-structured interviews conducted with audit professionals firms. This research evidence suggests that auditors’ skills and competence to perform engagement activities are assertively affected by BDA in audit methodology. Auditors benefit from being able to visualise audit evidence so they can use it to guide their professional judgement and decision making. We found evidence that the early stages of adopting data analytics and implementing are inefficient, but they save auditors’ time as the tools get more familiarised. Finally, we documented that auditing professionals can use analytics to gain more insight into clients’ business and offer them insights, which leads to confidence in clients.

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Author information

Authors and Affiliations

  1. Accounting Department, Faculty of Business, Al-Zaytoonah University of Jordan, Amman, Jordan

    Malik Abu Afifa & Isam Saleh

  2. Seneca College of Applied Arts and Technology, Toronto, Canada

    Yahya Marei

  3. Accounting Department, Faculty of Business, Isra University, Amman, Jordan

    Othman Hussein Othman

Authors
  1. Malik Abu Afifa
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  2. Yahya Marei
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  3. Isam Saleh
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  4. Othman Hussein Othman
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Corresponding author

Correspondence to Malik Abu Afifa .

Editor information

Editors and Affiliations

  1. Business Analytics and Information Systems, Faculty of Business, Al-Zaytoonah University of Jordan, Amman, Jordan

    Saad G. Yaseen

Appendix 1. List of Interview Participants

Appendix 1. List of Interview Participants

Code

Participant

Audit firm

Role(s)

P1

Partner—audit methodology

Big four

BDA development and implementation

P2

Partner—audit methodology

Big four

BDA development and implementation

P3

Partner—audit methodology

Mid-tier audit firm

BDA development and implementation

P4

Partner—audit assurance

Big four

BDA development and implementation

P5

Partner—audit assurance

Big FOUR

BDA development and implementation

P6

Partner—audit assurance

Mid-tier audit firm

BDA development and implementation

P7

Partner—audit assurance

Mid-tier audit firm

BDA development and implementation

P8

Partner—audit risk analytics

Big Four

BDA development and implementation

P9

Partner—audit risk analytics

Big four

BDA development and implementation

P10

Partner—audit risk analytics

Mid-tier audit firm

BDA development and implementation

P11

Partner—data assurance

Big four

BDA development and implementation

P12

Partner—data assurance

Big four

BDA development and implementation

P13

Partner—data assurance

Big four

BDA development and implementation

P14

Partner—data assurance

Mid-tier audit firm

BDA development and Implementation

P15

Partner—data assurance

Mid-tier audit firm

BDA development and implementation

P16

Partner—data assurance

Mid-tier audit firm

BDA development and implementation

P17

Data analytics auditor

Big four

BDA development and implementation

P18

Data analytics auditor

Big four

BDA development and implementation

P19

Data analytics auditor

Mid-tier audit firm

BDA development and implementation

P20

Data analytics auditor

Mid-tier audit firm

BDA development and implementation

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Abu Afifa, M., Marei, Y., Saleh, I., Othman, O.H. (2022). Big Data Analytics and Audit Quality: Evidence from Canada. In: Yaseen, S.G. (eds) Digital Economy, Business Analytics, and Big Data Analytics Applications. Studies in Computational Intelligence, vol 1010. Springer, Cham. https://doi.org/10.1007/978-3-031-05258-3_22

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