Riesgo operacional bancario aplicado con redes neuronales artificiales / Bank operational risk applied with artificial neural networks
Creators: name: Reyes, Eliseo Ramírez
Publisher: name: Zenodo
Year: 2021
Subjects: Finanzas
Banco
Inteligencia artificial
Finance
Banking
Artificial intelligence

description: <strong>Resumen </strong> La gestión de riesgo operacional ha sido ampliamente investigada en los últimos años, sin embargo, el Comité de Supervisión Bancaria de Basilea recomienda que los bancos desarrollen sistemas de medición que mejoren la comprensión del riesgo de sus actividades en comparación con las metodologías existentes. El objetivo de este capítulo es construir un modelo de Redes Neuronales Artificiales (RNA) que pueda ser integrado en la gestión de riesgo operacional en el sector bancario para analizar el desempeño de los eventos de pérdida. Con el uso de RNA se busca integrar una metodología no lineal que permita establecer una relación entre las actividades bancarias y las pérdidas económicas para mostrar un enfoque diferente en la evaluación de riesgos que pueda ser una alternativa a los métodos tradicionales. El capítulo se divide en dos secciones, la primera describe el proceso de la gestión de riesgo operacional desde la planeación hasta el control y mitigación de riesgos. La segunda sección muestra la aplicación de redes neuronales artificiales (RNA) como herramienta en la clasificación y medición de variables. Se concluye que el uso de RNA complementa a los métodos lineales para la cuantificación de variables en riesgo operacional. <strong>Abstract</strong> The operational risk management has been extensively researched in the past few years; however, The Basel Committee on Banking Supervision recommends that banks develop measurement systems that will improve the understanding of the risk of their activities compared to existing methodologies. The objective of this chapter is building an Artificial Neural Networks (ANN) model that can be incorporated into the operational risk management in banks to analyze the performance of loss events. The use of ANN is intended to integrate a non-lineal methodology that establishes a relationship between banking activities and financial losses to show a different approach to risk assessment which could be an alternative to the traditional methods. This chapter is divided in two sections, the first describes the process of operational risk management since planning until control and mitigation of risk. The second shows the artificial neural network application as tool in classifying and sizing variables. It is concluded that the use of artificial neural networks complements to lineal methods for quantifying variables in operational risk.
description: Código JEL: G21.
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