dc.contributor | Chaparro Cardona, Juan Camilo | |
dc.creator | Amaya Molina, Mateo | |
dc.date.accessioned | 2018-06-12T21:46:38Z | |
dc.date.accessioned | 2022-09-23T21:59:20Z | |
dc.date.available | 2018-06-12T21:46:38Z | |
dc.date.available | 2022-09-23T21:59:20Z | |
dc.date.created | 2018-06-12T21:46:38Z | |
dc.date.issued | 2017 | |
dc.identifier | http://hdl.handle.net/10784/12351 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3537429 | |
dc.description.abstract | The 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.publisher | Universidad EAFIT | |
dc.publisher | Economía | |
dc.publisher | Escuela de Economía y Finanzas. Departamento de Economía. | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.rights | Acceso abierto | |
dc.subject | Modelos predictivos | |
dc.subject | Árboles de decisión | |
dc.subject | Sistema de Administración de Riesgos de Lavado de Activos y Financiación del Terrorismo (SARLAFT) | |
dc.subject | Segmentación de clientes | |
dc.title | Segmentación 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.type | bachelorThesis | |
dc.type | info:eu-repo/semantics/bachelorThesis | |