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Pronóstico de incumplimientos de pago mediante máquinas de vectores de soporte: una aproximación inicial a la gestión del riesgo de crédito

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  • José Fernando Moreno Gutiérrez
  • Luis Fernando Melo Velandia

Abstract

Este documento describe la metodología desarrollada por Vapnik (1995), denominada máquinas de vectores de soporte (SVM, por sus siglas en inglés) y realiza dos aplicaciones al caso de clasificación de agentes para el otorgamiento de créditos a partir de sus características. El primer caso de estudio clasifica individuos de un banco alemán. En el segundo caso se pronostica el incumplimiento del pago de créditos comerciales otorgados a empresas colombianas utilizando las características iniciales del crédito. SVM se compara con dos metodologías utilizadas en el análisis de este tipo de problemas, regresión logística y análisis lineal discriminante. Los resultados arrojan un mejor desempeño en la predicción por parte de SVM respecto a las otras dos metodologías.

Suggested Citation

  • José Fernando Moreno Gutiérrez & Luis Fernando Melo Velandia, 2011. "Pronóstico de incumplimientos de pago mediante máquinas de vectores de soporte: una aproximación inicial a la gestión del riesgo de crédito," Borradores de Economia 677, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:borrec:677
    DOI: 10.32468/be.677
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    References listed on IDEAS

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    1. Thomas, Lyn C., 2009. "Consumer Credit Models: Pricing, Profit and Portfolios," OUP Catalogue, Oxford University Press, number 9780199232130.
    2. Christian Gourieroux & Joann Jasiak, 2007. "Introduction to The Econometrics of Individual Risk: Credit, Insurance, and Marketing," Introductory Chapters, in: The Econometrics of Individual Risk: Credit, Insurance, and Marketing, Princeton University Press.
    3. Kim, Hong Sik & Sohn, So Young, 2010. "Support vector machines for default prediction of SMEs based on technology credit," European Journal of Operational Research, Elsevier, vol. 201(3), pages 838-846, March.
    4. Lean Yu & Shouyang Wang & Kin Keung Lai & Ligang Zhou, 2008. "Bio-Inspired Credit Risk Analysis," Springer Books, Springer, number 978-3-540-77803-5, September.
    5. Matthew Brosnahan & Tan Chong Lee, 1989. "International convergence of capital measurement and capital standards for banks," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 52, march.
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    Cited by:

    1. Fabián Enrique Salazar Villano, 2013. "Cuantificación del riesgo de incumplimiento en créditos de libre inversión: un ejercicio econométrico para una entidad bancaria del municipio de Popayán, Colombia," Estudios Gerenciales, Universidad Icesi, December.

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    More about this item

    Keywords

    Clasificación; máquinas de aprendizaje; riesgo de crédito; support vector machines.;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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