dc.contributorChaparro Cardona, Juan Camilo
dc.creatorAmaya Molina, Mateo
dc.date.accessioned2018-06-12T21:46:38Z
dc.date.accessioned2022-09-23T21:59:20Z
dc.date.available2018-06-12T21:46:38Z
dc.date.available2022-09-23T21:59:20Z
dc.date.created2018-06-12T21:46:38Z
dc.date.issued2017
dc.identifierhttp://hdl.handle.net/10784/12351
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3537429
dc.description.abstractThe XXI century governments get the challenge to fortress their internal structure and controls against financial crimes of which they can be object -- The money laundering and the terrorism financing are the most frequently committed financial crimes around the world -- This type of activities is threatening the economic equilibrium in silence way turn and it´s representing a risk while talking about international trade relationships too -- The informatics advances in the field of data mining and statistics created a new complete landscape for those governments that try to get preventing controls and to identify that kind of activities -- These controls are required to those type of private organizations operating in the country in depending of the precise risk to each economic sector they belong -- This research develops an innovative method composed by the combination of techniques of data mining applying and the economics sector analysis looking for a possible answer to the financial sector entities controlling designed by SARLAFT in the Colombian government
dc.publisherUniversidad EAFIT
dc.publisherEconomía
dc.publisherEscuela de Economía y Finanzas. Departamento de Economía.
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAcceso abierto
dc.subjectModelos predictivos
dc.subjectÁrboles de decisión
dc.subjectSistema de Administración de Riesgos de Lavado de Activos y Financiación del Terrorismo (SARLAFT)
dc.subjectSegmentación de clientes
dc.titleSegmentación de clientes y definición de alertas para la prevención de riesgos de lavado de activos y financiación del terrorismo (SARLAFT): un estudio económico aplicado a entidad financiera colombiana en 2017
dc.typebachelorThesis
dc.typeinfo:eu-repo/semantics/bachelorThesis


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