Forensic analytics using cluster analysis: Detecting anomalies in data

Author

Clarence GOH, Singapore Management UniversityFollow
Benjamin Huan Zhou LEE, Singapore Management UniversityFollow
Gary PAN, Singapore Management UniversityFollow
Poh-Sun Seow, Singapore Management UniversityFollow

Publication Type

Journal Article

Version

submittedVersion

Publication Date

2-2021

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

Research Areas

Accounting Information System

Publication

Journal of Corporate Accounting and Finance

First Page

1

Last Page

8

ISSN

1044-8136

Identifier

10.1002/jcaf.22486?af=R

Publisher

Wiley: No OnlineOpen

Embargo Period

8-3-2021

Citation

GOH, Clarence; LEE, Benjamin Huan Zhou; PAN, Gary; and Seow, Poh-Sun. Forensic analytics using cluster analysis: Detecting anomalies in data. (2021). Journal of Corporate Accounting and Finance. 1-8.
Available at: https://ink.library.smu.edu.sg/soa_research/1896

Copyright Owner and License

Author

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.