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Exploring detection and prevention of money laundering with information technology

Geo Finna Aprilia (Master of Accounting Department, School of Accounting, Bina Nusantara University, Jakarta, Indonesia)
Meiryani (Accounting Department, School of Accounting, Bina Nusantara University, Jakarta, Indonesia)

Journal of Money Laundering Control

ISSN: 1368-5201

Article publication date: 30 November 2023

156

Abstract

Purpose

Regarding the magnitude of the impact caused by money laundering, the size of the organization and the many parties involved, this paper aims to explore the methods used in detecting money laundering, especially the use of technology.

Design/methodology/approach

This research is a literature review from various research sources originating from Pro-Quest, Emerald, Science Direct and Google Scholar.

Findings

The researchers found that the most widely used methods for detecting money laundering were artificial intelligence, machine learning, data mining and social network analysis.

Research limitations/implications

This research is expected to help the government or institutions such as the police, forensic accountants and investigative auditors in the fight against money laundering. This research is limited to only a few sources, and it is hoped that further research can explore more deeply related to other methods for detecting money laundering.

Originality/value

This paper discusses the methods that are widely used in detecting money laundering.

Keywords

Acknowledgements

The authors would like to thank Bina Nusantara University, Jakarta Indonesia for their funding in this paper.

Citation

Aprilia, G.F. and  , M. (2023), "Exploring detection and prevention of money laundering with information technology", Journal of Money Laundering Control, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JMLC-08-2023-0138

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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