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AI against money laundering networks: the Colombian case

Olmer Garcia-Bedoya (Department of Engineering, Universidad de Bogota Jorge Tadeo Lozano, Bogota, Colombia)
Oscar Granados (Department of Economics, Universidad de Bogota Jorge Tadeo Lozano, Bogota, Colombia)
José Cardozo Burgos (Todosistemas STI, Bogota, Colombia)

Journal of Money Laundering Control

ISSN: 1368-5201

Article publication date: 4 June 2020

Issue publication date: 25 May 2021

463

Abstract

Purpose

The purpose of this paper is to examine the artificial intelligence (AI) methodologies to fight against money laundering crimes in Colombia.

Design/methodology/approach

This paper examines Colombian money laundering situations with some methodologies of network science to apply AI tools.

Findings

This 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/implications

Access 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 implications

This 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 implications

This 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/value

The 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.

Keywords

Acknowledgements

The authors would like to thank anti-money laundering expert members in different financial organizations. This project received financial support of Minciencias from call for research proposals 816–2018, Project Grant 696481765389.

Citation

Garcia-Bedoya, O., Granados, O. and Cardozo Burgos, J. (2021), "AI against money laundering networks: the Colombian case", Journal of Money Laundering Control, Vol. 24 No. 1, pp. 49-62. https://doi.org/10.1108/JMLC-04-2020-0033

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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