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Generation of money laundering alerts based on complex networks [Generación de alertas de lavado de activos basadas en redes complejas: Una revisión sistemática]
dc.contributor.author | Ortíz M.M | |
dc.contributor.author | Marín L.M.G | |
dc.contributor.author | Villegas H.H.J | |
dc.contributor.author | Escobar C.C.P | |
dc.contributor.author | Montoya L.F.V. | |
dc.date.accessioned | 2022-09-14T14:33:47Z | |
dc.date.available | 2022-09-14T14:33:47Z | |
dc.date.created | 2021 | |
dc.identifier.issn | 16469895 | |
dc.identifier.uri | http://hdl.handle.net/11407/7470 | |
dc.description | International organizations face a highly complex task: to detect money-laundering operations, which, because of their illegality, tend to remain hidden from the authorities. One of the most valuable assets is the information centralized by these control bodies such as alerts generated by financial institutions based on transactional transactions, which, because of their large volume, requires an advanced strategy to identify unusual operations that, despite efforts, remain a challenge. For this reason, a systematic review of the literature on generating money-laundering alerts based on complex networks was developed. This review found that the analysis of complex networks is ideal given its ability to identify criminal patterns in a large volume of transactional data and also presents challenges for when the network is incomplete, and the origin or destination of resources is unknown. © 2021, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved. | eng |
dc.language.iso | spa | |
dc.publisher | Associacao Iberica de Sistemas e Tecnologias de Informacao | |
dc.relation.isversionof | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124405811&partnerID=40&md5=8bed5730123e3ee2e1687a5ce9d17a44 | |
dc.source | RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao | |
dc.title | Generation of money laundering alerts based on complex networks [Generación de alertas de lavado de activos basadas en redes complejas: Una revisión sistemática] | |
dc.type | Article | |
dc.rights.accessrights | info:eu-repo/semantics/restrictedAccess | |
dc.publisher.program | Ingeniería de Sistemas | |
dc.publisher.program | Ciencias Básicas | |
dc.type.spa | Artículo | |
dc.subject.keyword | Complex networks | eng |
dc.subject.keyword | Graph theory | eng |
dc.subject.keyword | Literature review | eng |
dc.subject.keyword | Money laundering | eng |
dc.relation.citationvolume | 2021 | |
dc.relation.citationissue | E43 | |
dc.relation.citationstartpage | 254 | |
dc.relation.citationendpage | 265 | |
dc.publisher.faculty | Facultad de Ingenierías | |
dc.publisher.faculty | Facultad de Ciencias Básicas | |
dc.affiliation | Ortíz, M.M., Estudiante Maestría en Modelación y Ciencia Computacional, Universidad de Medellín, Antioquia, Colombia | |
dc.affiliation | Marín, L.M.G., Facultad de Ingenierías, Universidad de Medellín, Antioquia, Colombia | |
dc.affiliation | Villegas, H.H.J., Facultad de Ciencias Básicas, Universidad de Medellín, Antioquia, Colombia | |
dc.affiliation | Escobar, C.C.P., Facultad de Ciencias Básicas, Universidad de Medellín, Antioquia, Colombia | |
dc.affiliation | Montoya, L.F.V., Grupo de Investigación Arkadius, Facultad de Ingenierías, Universidad de Medellín, Antioquia, Colombia | |
dc.relation.references | Amala Dhaya, M. D., Ravi, R., Multi feature behavior approximation model based efficient botnet detection to mitigate financial frauds (2020) Journal of Ambient Intelligence and Humanized Computing, , https://doi.org/10.1007/s12652-020-01677-w | |
dc.relation.references | Berlusconi, G., Calderoni, F., Parolini, N., Verani, M., Piccardi, C., Link prediction in criminal networks: A tool for criminal intelligence analysis (2016) PLoS ONE, 11 (4). , https://doi.org/10.1371/journal.pone.0154244 | |
dc.relation.references | Company, M., McKinsey & Company, , https://www.mckinsey.com/industries/financial-services/our-insights/banking-matters/network-analytics-and-the-fight-against-money-laundering#, (s.f). Obtenido de | |
dc.relation.references | De Moor, S., Vandeviver, C., Vander Beken, T., Assessing the missing data problem in criminal network analysis using forensic DNA data (2020) Social Networks, 61, pp. 99-106. , https://doi.org/10.1016/j.socnet.2019.09.003 | |
dc.relation.references | Diviák, T., Dijkstra, J. K., Snijders, T. A. B., Poisonous connections: a case study on a Czech counterfeit alcohol distribution network (2020) Global Crime, 21 (1), pp. 51-73. , https://doi.org/10.1080/17440572.2019.1645653 | |
dc.relation.references | Fronzetti Colladon, A., Remondi, E., Using social network analysis to prevent money laundering (2017) Expert Systems with Applications, 67, pp. 49-58. , https://doi.org/10.1016/j.eswa.2016.09.029 | |
dc.relation.references | Helmy, T. H., Zaki, M., Salah, T., Badran, K., Design of a monitor for detecting money laundering and terrorist financing (2016) Journal of Theoretical and Applied Information Technology, 85 (3), pp. 425-436. , https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962459616&partnerID=40&md5=7d026632557c7b124059fcd02dc9557e | |
dc.relation.references | Huang, D., Mu, D., Yang, L., Cai, X., CoDetect: Financial Fraud Detection with Anomaly Feature Detection (2018) IEEE Access, 6, pp. 19161-19174. , https://doi.org/10.1109/ACCESS.2018.2816564Luna-Pla,I.,&Nicolás-Carlock,J.R, (2020) | |
dc.relation.references | Corruption and complexity: a scientific framework for the analysis of corruption networks Applied Network Science, 5 (1). , https://doi.org/10.1007/s41109-020-00258-2 | |
dc.relation.references | Melo, C., (2019) Canal 1, , https://noticias.canal1.com.co/nacional/lavado-de-activos-en-2019-superaria-los-63-billones-denuncia-la-fiscalia/Meneghini, (3 de 12 de). Obtenido de C., Aziani, A., & Dugato, M. (2020) | |
dc.relation.references | Modeling the structure and dynamics of transnational illicit networks: an application to cigarette trafficking Applied Network Science, 5 (1). , https://doi.org/10.1007/s41109-020-00265-3 | |
dc.relation.references | Norbutas, L., Offline constraints in online drug marketplaces: An exploratory analysis of a cryptomarket trade network (2018) International Journal of Drug Policy, 56, pp. 92-100. , https://doi.org/10.1016/j.drugpo.2018.03.016 | |
dc.relation.references | Pienta, R., Hohman, F., Endert, A., Tamersoy, A., Roundy, K., Gates, C., Navathe, S., Chau, D. H., VIGOR: Interactive Visual Exploration of Graph Query Results (2018) IEEE Transactions on Visualization and Computer Graphics, 24 (1), pp. 215-225. , https://doi.org/10.1109/TVCG.2017.2744898 | |
dc.relation.references | Pritheega, M., Complex network tools to enable identification of a criminal community (2016) Bulletin of the Australian Mathematical Society, 94 (2), pp. 350-352. , https://doi.org/10.1017/S000497271600040X | |
dc.relation.references | Ren, X.-L., Gleinig, N., Helbing, D., Antulov-Fantulin, N., Generalized network dismantling (2019) Proceedings of the National Academy of Sciences of the United States of America, 116 (14), pp. 6554-6559. , https://doi.org/10.1073/pnas.1806108116 | |
dc.relation.references | Summers, L., Johnson, S. D., Does the Configuration of the Street Network Influence Where Outdoor Serious Violence Takes Place? Using Space Syntax to Test Crime Pattern Theory (2017) Journal of Quantitative Criminology, 33 (2), pp. 397-420. , https://doi.org/10.1007/s10940-016-9306-9 | |
dc.relation.references | (2018), https://www.uiaf.gov.co/sistema_nacional_ala_cft/lavado_activos_financiacion_29271/prevenccion_deteccion_la_ft, (23 de 10 de). UIAF. Obtenido de | |
dc.relation.references | Wandelt, S., Sun, X., Feng, D., Zanin, M., Havlin, S., A comparative analysis of approaches to network-dismantling (2018) Scientific Reports, 8 (1). , https://doi.org/10.1038/s41598-018-31902-8 | |
dc.relation.references | Zimiles, E., (2019) World Economic Forum, , https://www.weforum.org/agenda/2019/01/how-ai-can-knock-the-starch-out-of-money-laundering/, (Enero 17). Retrieved from World Economic Forum | |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | |
dc.type.driver | info:eu-repo/semantics/article | |
dc.identifier.reponame | reponame:Repositorio Institucional Universidad de Medellín | |
dc.identifier.repourl | repourl:https://repository.udem.edu.co/ | |
dc.identifier.instname | instname:Universidad de Medellín |
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