Financial fraud detection: the use of visualization techniques in credit card fraud and money laundering domains

Mark E. Lokanan

Journal of Money Laundering Control, 2022, vol. 26, issue 3, 436-444

Abstract: Purpose - This paper aims to reviews the literature on applying visualization techniques to detect credit card fraud (CCF) and suspicious money laundering transactions. Design/methodology/approach - In surveying the literature on visual fraud detection in these two domains, this paper reviews: the current use of visualization techniques, the variations of visual analytics used and the challenges of these techniques. Findings - The findings reveal how visual analytics is used to detect outliers in CCF detection and identify links to criminal networks in money laundering transactions. Graph methodology and unsupervised clustering analyses are the most dominant types of visual analytics used for CCF detection. In contrast, network and graph analytics are heavily used in identifying criminal relationships in money laundering transactions. Originality/value - Some common challenges in using visualization techniques to identify fraudulent transactions in both domains relate to data complexity and fraudsters’ ability to evade monitoring mechanisms.

Keywords: Financial crimes; Visualization; Money laundering; Knowledge discovery (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
Access to full text is restricted to subscribers

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:eme:jmlcpp:jmlc-04-2022-0058

DOI: 10.1108/JMLC-04-2022-0058

Access Statistics for this article

Journal of Money Laundering Control is currently edited by Dr Li Hong Xing and Prof Barry Rider

More articles in Journal of Money Laundering Control from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().