Examinando por Materia "Machine learning techniques"

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    Ítem
    Medición del riesgo sistémico intra-bancario
    (Universidad EAFIT, 2020) Cadavid Betancur, Lixander Felipe; Restrepo Tobón, Diego Alexander
    Systemic risk is understood as the risk that a complete complex system collapses as a result of the decisions and actions taken by the individual agents that are part of the system. It is a subject of high importance for both the real sector and the financial system, since a contribution is made to the management, administration and mitigation of credit and contagion risk. A model is proposed through machine learning techniques with the objective of analyzing from the transactional and credit risk, the expected impact of financial difficulties that arise in clients with high portfolio exposures and contagion risk with other customers. From a credit risk management and machine learning approach, recommendations of good practices are proposed in this article to contribute to the mitigation of this type of risk.