A Proposal to Fuzzify Categorical Variables in Operational Risk Management

  • Concetto Elvio Bonafede
  • Paola CerchielloEmail author
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


This contribution is deemed in the view of the authors, as a methodological proposal in order to employ the well know fuzzy approach in a context of operational risk management. Even though the available data can not be considered native fuzzy, we show that modelling them according to fuzzy intervals is useful from two point of view: it allows to take into account and to exploit more information and, on the other hand, either unsupervised or supervised models applied to this kind of data present comparatively good performance. The paper shows how to obtain fuzzy data moving from a classical database and later on the application of fuzzy principal components analysis and linear regression analysis.


Membership Function Operational Risk Target Variable Fuzzy Approach Fuzzy Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors acknowledge financial support from national Italian grant MIUR-FIRB 2006–2009 and European grant EU-IP MUSING (contract number 027097). The authors also thank Chiara Cornalba for the construction of the hierarchical maps of “Problem description” variable.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.University of PaviaPaviaItaly

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