Publication Type
Journal Article
Version
submittedVersion
Publication Date
4-2021
Abstract
Cluster analysis is a data analytics technique that can help forensic accountants effectively detect anomalies in complex financial datasets. This article provides a description of clustering analysis, discusses how it can be implemented to detect anomalies in data, and illustrates its use through a worked example using the Tableau software.
Keywords
Forensic accounting, data analytics, clustering, Tableau
Discipline
Accounting | Management Information Systems
Research Areas
Accounting Information System
Publication
Journal of Corporate Accounting and Finance
Volume
32
Issue
2
First Page
154
Last Page
161
ISSN
1044-8136
Identifier
10.1002/jcaf.22486
Publisher
Wiley
Embargo Period
8-3-2021
Citation
GOH, Clarence; LEE, Benjamin; PAN, Gary; and Seow, Poh-Sun.
Forensic analytics using cluster analysis: Detecting anomalies in data. (2021). Journal of Corporate Accounting and Finance. 32, (2), 154-161.
Available at: https://ink.library.smu.edu.sg/soa_research/1896
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1002/jcaf.22486