Embedding process mining into financial statement audits
Michael Werner,
Michael Wiese and
Annalouise Maas
International Journal of Accounting Information Systems, 2021, vol. 41, issue C
Abstract:
The audit of financial statements is a complex and highly specialized process. Digitalization and the increasing automation of transaction processing create new challenges for auditors who carry out those audits. New data analysis techniques offer the opportunity to improve the auditing of financial statements and to overcome the limitations of traditional audit procedures when faced with increasingly large amounts of financially relevant transactions that are processed automatically or semi-automatically by computer systems. This study discusses process mining as a novel data analysis technique which has been receiving increased attention in the audit practice. Process mining makes it possible to analyse business processes in an automated manner. This study investigates how process mining can be integrated into contemporary audits by reviewing the relevant audit standards and incorporating the results from a field study. It demonstrates the feasibility of embodying process mining within financial statement audits in accordance with contemporary audit standards and generally accepted audit practices. Implementation of process mining increases the reliability of the audit conclusions and improves the robustness of audit evidence by replacing manual audit procedures. Process mining as novel data mining technique provides auditors the means to keep pace with current technological developments and challenges.
Keywords: Process mining; Data analytics; Audit of financial statements; Big data, Data science, Business intelligence; Business process modelling; Enterprise resource planning systems; Field study (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1467089521000166
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ijoais:v:41:y:2021:i:c:s1467089521000166
DOI: 10.1016/j.accinf.2021.100514
Access Statistics for this article
International Journal of Accounting Information Systems is currently edited by S.V. Grabski
More articles in International Journal of Accounting Information Systems from Elsevier
Bibliographic data for series maintained by Catherine Liu ().