Skip to main content

LUP Student Papers

LUND UNIVERSITY LIBRARIES

Big Data Analytics and Auditing - Implementation and knowledge

Bengtsson, Emelie LU and Zago, Mikael LU (2019) BUSN79 20191
Department of Business Administration
Abstract
Purpose: The purpose of the thesis is to increase the understanding of phenomena surrounding the implementation of Big Data Analytics into the audit methodology, within the context of medium and large-sized audit firms, and how auditing knowledge and its dissemination affects the implementation process.

Theoretical perspectives: An analytical model based on previous research regarding Big Data Analytics and Auditing, The Audit Profession, Legitimacy Theory in the context of the implementation of new technology, Audit Knowledge and Knowledge sharing.

Methodology: An iterative qualitative thesis, where a literature review was conducted to scope the field, find areas of interest and gaps to cover. Lacking research covering Big Data... (More)
Purpose: The purpose of the thesis is to increase the understanding of phenomena surrounding the implementation of Big Data Analytics into the audit methodology, within the context of medium and large-sized audit firms, and how auditing knowledge and its dissemination affects the implementation process.

Theoretical perspectives: An analytical model based on previous research regarding Big Data Analytics and Auditing, The Audit Profession, Legitimacy Theory in the context of the implementation of new technology, Audit Knowledge and Knowledge sharing.

Methodology: An iterative qualitative thesis, where a literature review was conducted to scope the field, find areas of interest and gaps to cover. Lacking research covering Big Data Analytics in the context of auditing was discovered and an area of interest decided. Semi-structured interviews were conducted to capture and analyse practitioners perceived notions regarding the implementation of Big Data Analytics into the audit methodology.

Empirical foundation: 11 interviews were conducted with 13 people within the audit profession, with roles including senior analytics, certified auditors, and associates, see Appendix 3 for full disclosure.

Conclusions: The implementation of Big Data Analytics into the audit methodology is perceived to enable improvements in the form of increased audit quality and efficiency, albeit these opportunities are dependent on the profession’s ability to handle the inherent risks and issues associated, where this thesis has identified perceived risks including expanded expectation gap, deprofessionalisation, and two knowledge gaps. (Less)
Please use this url to cite or link to this publication:
author
Bengtsson, Emelie LU and Zago, Mikael LU
supervisor
organization
course
BUSN79 20191
year
type
H1 - Master's Degree (One Year)
subject
keywords
Big Data Analytics, Big Data, Auditing, Audit knowledge, Knowledge sharing
language
English
id
8989224
date added to LUP
2019-09-30 13:51:02
date last changed
2019-09-30 13:51:02
@misc{8989224,
  abstract     = {{Purpose: The purpose of the thesis is to increase the understanding of phenomena surrounding the implementation of Big Data Analytics into the audit methodology, within the context of medium and large-sized audit firms, and how auditing knowledge and its dissemination affects the implementation process.

Theoretical perspectives: An analytical model based on previous research regarding Big Data Analytics and Auditing, The Audit Profession, Legitimacy Theory in the context of the implementation of new technology, Audit Knowledge and Knowledge sharing.

Methodology: An iterative qualitative thesis, where a literature review was conducted to scope the field, find areas of interest and gaps to cover. Lacking research covering Big Data Analytics in the context of auditing was discovered and an area of interest decided. Semi-structured interviews were conducted to capture and analyse practitioners perceived notions regarding the implementation of Big Data Analytics into the audit methodology.

Empirical foundation: 11 interviews were conducted with 13 people within the audit profession, with roles including senior analytics, certified auditors, and associates, see Appendix 3 for full disclosure.

Conclusions: The implementation of Big Data Analytics into the audit methodology is perceived to enable improvements in the form of increased audit quality and efficiency, albeit these opportunities are dependent on the profession’s ability to handle the inherent risks and issues associated, where this thesis has identified perceived risks including expanded expectation gap, deprofessionalisation, and two knowledge gaps.}},
  author       = {{Bengtsson, Emelie and Zago, Mikael}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Big Data Analytics and Auditing - Implementation and knowledge}},
  year         = {{2019}},
}