Exploring detection and prevention of money laundering with information technology
| Date | 30 November 2023 |
| Pages | 995-1004 |
| DOI | https://doi.org/10.1108/JMLC-08-2023-0138 |
| Published date | 30 November 2023 |
| Author | Geo Finna Aprilia,Meiryani |
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, and
Meiryani
Accounting Department, School of Accounting, Bina Nusantara University,
Jakarta, Indonesia
Abstract
Purpose –Regarding themagnitude of the impact caused by money laundering,the size of the organization
and the many parties involved, thispaper aims to explore the methods used in detecting money laundering,
especiallythe use of technology.
Design/methodology/approach –This research is a literature reviewfrom various research sources
originatingfrom Pro-Quest, Emerald, Science Directand Google Scholar.
Findings –The researchersfound that the most widely used methods for detecting moneylaundering were
artificialintelligence, machine learning, data miningand social network analysis.
Research limitations/implications –This research is expectedtohelp 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 methodsfor detecting money laundering.
Originality/value –This paper discusses the methods that are widely used in detecting money laundering.
Keywords Money laundering, Technology, Artificial intelligence, Machine learning, Data mining,
Social network analysis
Paper type Literature review
Introduction
Based on data fromthe Corruption Perceptions Index (CPI) 2022, the state of Indonesia is
ranked 110 out of 180 countries on a global scale for the most corrupt country. In addition,
Indonesia’s corruption perceptions index (CPI) score has also decreased to 34 from 100 in
2022 (where a scoreof 0 means very corrupt and 100 means very clean). Ninety-two per cent
of people consider government corruption as a big problem (Transparency International,
2022). The criminal act of corruption is a crime directly related to money laundering (Veng
Mei Leong, 2007in Meiryani and Warganegara,2022).
The origins of the AML framework globally were fueled by states’recognition of the
negative impact organized crime has on society. Organized crime groups are involved in illegal
activities that generate illicit funds, which necessitate the group’s involvement in money
laundering. Money laundering facilitates the “cleaning”of these funds, which can then be used
in a legitimate economy (Gikonyo, 2018).
The authors would like to thank Bina Nusantara University, Jakarta Indonesia for their funding in
this paper.
Money
laundering
995
Journalof Money Laundering
Control
Vol.27 No. 6, 2024
pp. 995-1004
© Emerald Publishing Limited
1368-5201
DOI 10.1108/JMLC-08-2023-0138
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1368-5201.htm
Get this document and AI-powered insights with a free trial of vLex and Vincent AI
Get Started for FreeStart Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting