Publicación:
Identificación de las principales prácticas implementadas por las entidades financieras para combatir el fraude financiero

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dc.contributor.advisorPatiño Castro, Omar Alonso
dc.contributor.authorCárdenas Saavedra, Jeison Felipe
dc.contributor.authorCárdenas Justinico, Jessica Lorena
dc.contributor.juryGuerrero Cabarcas, Mauricio Javier
dc.contributor.juryDelgado Ortiz, Sandra Marcela
dc.creator.id1014263104
dc.creator.id1094890340
dc.date.accessioned2025-08-17T23:40:15Z
dc.date.issued2025-07-06
dc.description.abstractEl presente trabajo analiza las principales prácticas implementadas por las entidades financieras para combatir el fraude financiero, con un enfoque especial en el Banco Itaú Colombia. Este fenómeno, potenciado por la digitalización y los avances tecnológicos, representa un desafío creciente tanto a nivel global como en América Latina. Mediante una revisión sistemática de literatura y el análisis de casos reales, se identificaron patrones de fraude interno y externo, así como metodologías basadas en aprendizaje automático, minería de datos y técnicas avanzadas como redes neuronales y algoritmos de detección de anomalías. Los resultados muestran que las herramientas tecnológicas, combinadas con controles internos efectivos y una cultura organizacional y una estructura de Gobierno de Datos sólida, son clave para mitigar los riesgos de fraude y mejorar la sostenibilidad de las operaciones bancarias. Este estudio ofrece recomendaciones prácticas y un marco metodológico para fortalecer la gestión de riesgos financieros en las instituciones.spa
dc.description.abstractThe present study analyzes the main practices implemented by financial institutions to combat financial fraud, with a particular focus on Banco Itaú Colombia. This phenomenon, driven by digitalization and technological advancements, poses a growing challenge both globally and in Latin America. Through a systematic literature review and the analysis of real cases, patterns of internal and external fraud were identified, as well as methodologies based on machine learning, data mining, and advanced techniques such as neural networks and anomaly detection algorithms. The results demonstrate that technological tools, combined with effective internal controls, a strong organizational culture, and a robust Data Governance structure, are essential to mitigating fraud risks and improving the sustainability of banking operations. This study provides practical recommendations and a methodological framework to strengthen financial risk management within institutions.eng
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Administración de Empresas - MBAspa
dc.description.tableofcontents1. Introducción 1.1. Tema de Investigación 1.2. Problema de Investigación 1.1.1. Antecedentes 1.1.2. Planteamiento del Problema 1.1.3. Pregunta de Investigación 2. Objetivos de investigación 2.1. Objetivo general 2.2. Objetivos específicos 3. Justificación 4. Marco Institucional 4.1. Sector Financiero Colombiano y Posición en el Mercado 4.2. Productos y Servicios 4.3. Tendencias y Retos del Sector 5. Marco Conceptual y Contextual 5.1. Definición de Fraude 5.1.1. Fraude Interno 5.1.2. Prevención y Detección 6. Diseño Metodológico de la Consultoría para el Banco Itaú 6.1. Enfoque de la Investigación 6.2. Fases de la Consultoría 6.3. Procedimientos y Técnicas para el Diagnóstico 6.3.1. Procedimientos 6.3.2. Técnicas 7. Diagnostico Organizacional 7.1. Revisión de la literatura científica sobre las prácticas financieras bajo el contexto mundial 7.2. Investigación sobre casos reales de fraude en entidades financieras 7.3. Generación de la metodología para la selección de modelos de predicción de fraudes financieros 7.4. Procesamiento de Datos Factores Clave para una Gobernanza de Datos Efectiva Gobernanza de Datos como Defensa Contra el Fraude Normativas y Calidad de Datos 8. Resultados de la Solución 8.1. Metodología para la selección del modelo óptimo de detección de fraude 8.1.1. Curar 8.1.2. Comprender 8.1.3. Curar y Comprender 8.1.4. Selección del Modelo 8.1.5. Proteger 8.1.6. Proteger y Comprender 9. Conclusiones y Recomendaciones 9.1. Conclusiones 9.2. Recomendaciones 10. Referencias Bibliográficas Anexo A: Matriz de Consulta Bibliográficaspa
dc.description.tableofcontents1. Introduction 1.1. Research Topic 1.2. Research Problem 1.1.1. Background 1.1.2. Problem Statement 1.1.3. Research Question 2. Research Objectives 2.1. General Objective 2.2. Specific Objectives 3. Justification 4. Institutional Framework 4.1. Colombian Financial Sector and Market Position 4.2. Products and Services 4.3. Trends and Challenges in the Sector 5. Conceptual and Contextual Framework 5.1. Definition of Fraud 5.1.1. Internal Fraud 5.1.2. Prevention and Detection 6. Methodological Design of the Consulting Firm for Itaú Bank 6.1. Research Approach 6.2. Consulting Phases 6.3. Diagnostic Procedures and Techniques 6.3.1. Procedures 6.3.2. Techniques 7. Organizational Diagnosis 7.1. Review of the Scientific Literature on Financial Practices in a Global Context 7.2. Research on Actual Fraud Cases in Financial Institutions 7.3. Generation of the Methodology for Selecting Financial Fraud Prediction Models 7.4. Data Processing Key Factors for Effective Data Governance Data Governance as a Defense Against Fraud Regulations and Data Quality 8. Solution Results 8.1. Methodology for Selecting the Optimal Fraud Detection Model 8.1.1. Curation 8.1.2. Understanding 8.1.3. Curation and Understanding 8.1.4. Model Selection 8.1.5. Protection 8.1.6. Protection and Understanding 9. Conclusions and Recommendations 9.1. Conclusions 9.2. Recommendations 10. References Annex A: Reference Reference Matrixeng
dc.formatpdf
dc.format.extent116 páginas
dc.format.mediumRecurso electrónicospa
dc.format.mimetypeapplication/pdf
dc.identifier.instnameinstname:Universidad Eanspa
dc.identifier.localBDM-MBA
dc.identifier.reponamereponame:Repositorio Institucional Biblioteca Digital Minervaspa
dc.identifier.repourlrepourl:https://repository.ean.edu.co/
dc.identifier.urihttps://hdl.handle.net/10882/15012
dc.language.isospa
dc.publisher.facultyFacultad de Administración, Finanzas y Ciencias Económicasspa
dc.publisher.programMaestría en Administración de Empresas - MBAspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
dc.rights.localAbierto (Texto Completo)spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/
dc.subject.armarcInstituciones financierasspa
dc.subject.armarcFraude de valoresspa
dc.subject.armarcDelitos económicosspa
dc.subject.armarcInstituciones financieras -- Prácticas corruptasspa
dc.subject.armarcCompetencia económica deslealspa
dc.subject.proposalFraude financierospa
dc.subject.proposalDetección de anomalíasspa
dc.subject.proposalModelos predictivosspa
dc.subject.proposalGobierno de datosspa
dc.subject.proposalControl internospa
dc.subject.proposalFinancial fraudeng
dc.subject.proposalAnomaly detectioneng
dc.subject.proposalPredictive modelseng
dc.subject.proposalData governanceeng
dc.subject.proposalInternal controleng
dc.titleIdentificación de las principales prácticas implementadas por las entidades financieras para combatir el fraude financierospa
dc.titleIdentification of the main practices implemented by financial institutions to combat financial fraudeng
dc.typeTrabajo de grado - Maestríaspa
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dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.contentText
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.otherTrabajo de grado - Maestría
dc.type.redcolhttp://purl.org/redcol/resource_type/TM
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePublication
person.affiliation.nameMaestría en Administración de Empresas - MBA
person.affiliation.nameMaestría en Inteligencia de Negocios - Virtual
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