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AI against money laundering networks: the Colombian case

AI against money laundering networks: the Colombian case The purpose of this paper is to examine the artificial intelligence (AI) methodologies to fight against money laundering crimes in Colombia.Design/methodology/approachThis paper examines Colombian money laundering situations with some methodologies of network science to apply AI tools.FindingsThis paper identifies the suspicious operations with AI methodologies, which are not common by number, quantity or characteristics within the economic or financial system and normal practices of companies or industries.Research limitations/implicationsAccess to financial institutions’ data was the most difficult element for research because affect the implementation of a set of different algorithms and network science methodologies.Practical implicationsThis paper tries to reduce the social and economic implications from money laundering (ML) that result from illegal activities and different crimes against inhabitants, governments, public resources and financial systems.Social implicationsThis paper proposes a software architecture methodology to fight against ML and financial crime networks in Colombia which are common in different countries. These methodologies complement legal structure and regulatory framework.Originality/valueThe contribution of this paper is how within the flow already regulated by financial institutions to manage the ML risk, AI can be used to minimize and identify this kind of risk. For this reason, the authors propose to use the graph analysis methodology for monitoring and identifying the behavior of different ML patterns with machine learning techniques and network science methodologies. These methodologies complement legal structure and regulatory framework. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Money Laundering Control Emerald Publishing

AI against money laundering networks: the Colombian case

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References (18)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1368-5201
eISSN
1368-5201
DOI
10.1108/jmlc-04-2020-0033
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to examine the artificial intelligence (AI) methodologies to fight against money laundering crimes in Colombia.Design/methodology/approachThis paper examines Colombian money laundering situations with some methodologies of network science to apply AI tools.FindingsThis paper identifies the suspicious operations with AI methodologies, which are not common by number, quantity or characteristics within the economic or financial system and normal practices of companies or industries.Research limitations/implicationsAccess to financial institutions’ data was the most difficult element for research because affect the implementation of a set of different algorithms and network science methodologies.Practical implicationsThis paper tries to reduce the social and economic implications from money laundering (ML) that result from illegal activities and different crimes against inhabitants, governments, public resources and financial systems.Social implicationsThis paper proposes a software architecture methodology to fight against ML and financial crime networks in Colombia which are common in different countries. These methodologies complement legal structure and regulatory framework.Originality/valueThe contribution of this paper is how within the flow already regulated by financial institutions to manage the ML risk, AI can be used to minimize and identify this kind of risk. For this reason, the authors propose to use the graph analysis methodology for monitoring and identifying the behavior of different ML patterns with machine learning techniques and network science methodologies. These methodologies complement legal structure and regulatory framework.

Journal

Journal of Money Laundering Control – Emerald Publishing

Published: May 25, 2021

Keywords: Money laundering; Artificial intelligence; Software architecture; Financial crime networks

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