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Modeling of Operative Risk Using Fuzzy Expert Systems

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Fuzzy Cognitive Maps

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 247))

Abstract

This study is focusing on the modeling of operative loss exposure of the Allowances and Retirement Funds with the use of a Fuzzy Expert System, which evaluates the environmental and managerial factors, this allow obtain a qualification about the possibility that the company incurs in operative losses. The system can be very useful either when the quantitative information is limited due to the discrete character of the risk events or where the information about the risk factors are associated to expert’s knowledge, for these reasons the modeling using formal statistical tools is difficult. Too we propose, a simple methodology to complete the knowledge matrix of the Fuzzy Expert System which combines the scoring method with the expert knowledge that allows obtain the rules of system in a simple and quick way. This extraction method saves time in the modeling of complex systems where many variable interact and where there are restrictions with the expert interactions. These systems allow having a structured vision of the sources of operational risk and where the manager should concentrate efforts to diminish the exposure. The Fuzzy Expert System can help to complement the operative risk analysis carried out with quantitative methods as Extreme value theory or Montecarlo simulation.

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Authors and Affiliations

  1. Minas Faculty, National University of Colombia,  

    Santiago Medina Hurtado

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  1. Santiago Medina Hurtado
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Editors and Affiliations

  1. University of Aegean, Chios, Greece

    Michael Glykas

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Hurtado, S.M. (2010). Modeling of Operative Risk Using Fuzzy Expert Systems. In: Glykas, M. (eds) Fuzzy Cognitive Maps. Studies in Fuzziness and Soft Computing, vol 247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03220-2_6

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  • DOI: https://doi.org/10.1007/978-3-642-03220-2_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03219-6

  • Online ISBN: 978-3-642-03220-2

  • eBook Packages: EngineeringEngineering (R0)

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