English, Article, Journal or magazine article edition: Measuring and managing credit risk in SMEs: a quantitative and qualitative rating model Ivan DE NONI; Antonio LORENZON; Luigi ORSI

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Bookmark: http://trove.nla.gov.au/version/58419
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Measuring and managing credit risk in SMEs: a quantitative and qualitative rating model
Author
  • Ivan DE NONI
  • Antonio LORENZON
  • Luigi ORSI
Physical Description
  • preprint
Notes
  • The main aim of this paper is to develop a qualitative and quantitative credit risk rating model for SMEs. The scope of this model is to assign, through a discriminant function (see Altman,1969), a synthetic judgment of the firm management ( ). First of all it must characterize variables that multiplied for a weighted coefficient allow us to determine a score of the analyzed enterprises. The classification is based on a discriminating function that maximize the variance of the variables among the firms of two groups and to minimize the variance among the firms of the same group. An important aspect of the model is its ability to enclose in the judgment of rating also the qualitative part. The objective is to modify the quantitative score including the qualitative judgments that emerge from a qualitative questionnaire. The final rating, therefore, is constructed assigning the final score (quantitative plus qualitative) to the class of rating that it includes such value. So a synthetic judgment of the solvency, the solidity and the forecasts is supplied about the firm analysis. In conclusion we can say that the obtained results confirm the reliability of the model. The error percentage, in fact, is only of 13.65% for the performing firm and 8.91% for the non performing. Further analyses have demonstrated that the model turns out reliable also in relation to possible distortions generated from dimensional (analysis for number of employers) and geographical (analysis for province) effects. Contrarily a surveying on industry does not give the same results. Various industry are characterize from different variability coefficients and it implies a meaningful sectorial effect
  • SMEs, Rating Model, Competitiveness, Networking
  • RePEc:mil:wpdepa:2007-36
Language
  • English
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