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2019 | OriginalPaper | Buchkapitel

15. Fighting Against Money Laundering: A Systematic Mapping

verfasst von : Bruno Luiz Kreutz Barroso, Fábio Mangueira, Methanias Colaço Júnior

Erschienen in: 16th International Conference on Information Technology-New Generations (ITNG 2019)

Verlag: Springer International Publishing

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Abstract

Context: Money Laundering (ML) is a global crime that has a close relation with other crimes, such as: illegal drug trading, terrorism or arms trafficking. Criminals in today’s technology-driven society use every means available at their disposal to launder the profit made from their illegal activities. In response, international anti-money laundering (AML) efforts are made with AML systems. Objective: Identify and systematize the approaches, techniques and algorithms used in Computer Science (CS) to fight ML, besides identifying the trends in the field. Method: A systematic literature mapping was conducted to analyze the scientific research in the field. Results: The main approaches were identified, supervised classifiers and clusters, along with the trend of papers published over the years. China was the country with the highest number of published papers. Conclusion: The most relevant studies in such research line adopt data mining and machine learning techniques using clusters and classifiers. The state of the art was mapped, making it clear that it is an area of interest for researchers around the world with growth potential. We believe that this work is relevant to the academy, governments and the community at large, presenting them with trends in the detection of money laundering.

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Titel: Fighting Against Money Laundering: A Systematic Mapping
verfasst von: Bruno Luiz Kreutz Barroso
Fábio Mangueira
Methanias Colaço Júnior
Verlag: Springer International Publishing
Buch: 16th International Conference on Information Technology-New Generations (ITNG 2019)
Print ISBN: 978-3-030-14069-4

Electronic ISBN: 978-3-030-14070-0

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-14070-0_15

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