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Machine learning methodologies against money laundering in non-banking correspondents
dc.contributor.advisor | García Bedoya, Olmer | |
dc.coverage.spatial | Colombia | spa |
dc.creator | Guevara Pérez, Jorge Ivan | |
dc.creator | Granados, Oscar | |
dc.date.accessioned | 2021-02-12T16:57:49Z | |
dc.date.available | 2021-02-12T16:57:49Z | |
dc.date.created | 2021-02-07 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12010/17251 | |
dc.description.abstract | Las actividades de lavado de activos son el resultado de la corrupción, actividades ilegales y crimen organizado que afectan la dinámica social e involucra, directa e indirectamente a varias comunidades a través de diferentes mecanismos de blanqueo de dinero ilícito. En este artículo, proponemos un enfoque de aprendizaje automático para el análisis de actividades sospechosas en corresponsales bancarios, un tipo de agente financiero que desarrolla transacciones financieras para clientes bancarios específicos. Este artículo utiliza varios algoritmos para identificar anomalías en un conjunto de transacciones de un corresponsal bancario durante 2019 para una ciudad intermediaria en Colombia. Nuestros resultados muestran que algunas metodologías son más apropiadas que otros para este caso y facilita la identificación de las anomalías y transacciones sospechosas en este tipo de intermediario financiero. | spa |
dc.format.extent | 17 páginas | spa |
dc.format.mimetype | application/pdf | spa |
dc.language.iso | eng | spa |
dc.publisher | Universidad de Bogotá Jorge Tadeo Lozano | spa |
dc.source | instname:Universidad de Bogotá Jorge Tadeo Lozano | spa |
dc.source | reponame:Expeditio Repositorio Institucional UJTL | spa |
dc.subject | Transacciones | spa |
dc.subject | Corrupción | spa |
dc.title | Machine learning methodologies against money laundering in non-banking correspondents | spa |
dc.type.local | Trabajo de grado de maestría | spa |
dc.subject.lemb | Lavado de activos | spa |
dc.subject.lemb | Narcotraficantes | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | spa |
dc.rights.local | Abierto (Texto Completo) | spa |
dc.subject.keyword | Corruption | spa |
dc.identifier.repourl | http://expeditio.utadeo.edu.co | spa |
dc.creator.degree | Magíster en Ingeniería y Analítica de Datos | spa |
dc.publisher.program | Maestría en Ingeniería y Analítica de Datos | spa |
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dc.description.hashtag | #lavadoDeActivos | spa |
dc.description.hashtag | #TransaccionesFinancieras | spa |
dc.description.abstractenglish | The activities of money laundering are a result of corruption, illegal activities, and organized crime that affect social dynamics and involved, directly and indirectly, several communities through different mechanisms to launder illegal money. In this article, we propose a machine learning approach to the analysis of suspicious activities in nonbanking correspondents, a type of financial agent that develops some financial transactions for specific banking customers. This article uses several algorithms to identify anomalies in a transaction set of a nonbanking correspondent during 2019 for an intermediary city in Colombia. Our results show that some methodologies are more appropriate than others for this case and facilitate to identify the anomalies and suspicious transactions in this kind of financial intermediary. | spa |
dc.type.driver | info:eu-repo/semantics/masterThesis | spa |
dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | spa |