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Contingencies For Measurement Of The Credit Risk

Listed author(s):
  • Marinela BARBULESCU

    ()

    (University of Pitesti, Faculty of Economics, Romania)

  • Alina HAGIU

    ()

    (University of Pitesti, Faculty of Economics, Romania)

  • Cristina BALDAN

    ()

    (University of Pitesti, Faculty of Economics, Romania)

The Global Financial Crisis, which affected various banks, some of them very important banks, highlighted the importance of an accurate credit risk measurement in order to be able to overcome it. There are a variety of such credit risk measurement models, so we can say that banks face a real dilemma when having to choose the most appropriate one. The aim of this paper is to examine the most popular methods used to measure the credit risk and to identify the strengths and the weaknesses of each one of it. The research was accomplished from a double perspective, in which the conceptual methodological approach is correlated to a variety of references to practical actions aiming the measurement and the prevention of credit risk. The study includes the presentation of the objectives of credit risk analysis, the most appropriate moments for doing such an analysis, the steps that have to be done in order to measure the credit risk, the errors that can overcome in the credit risk measurement system, generated by the misclassifications of the studied company, and the presentation of the specific information of financial creditors. The findings expressed in this paper were mainly the result of a qualitative analysis which showed that there is no best model for credit risk measurement, each one having both strengths and weaknesses, some providing a comprehensive analysis of the individual customer’s financial strength others allowing banks permanently monitor fluctuating default risk and identify the possibly problems at an early stage.

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Article provided by University of Pitesti in its journal Scientific Bulletin - Economic Sciences.

Volume (Year): 14 (2015)
Issue (Month): 3 ()
Pages: 60-65

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Handle: RePEc:pts:journl:y:2015:i:3:p:60-65
Contact details of provider: Web page: http://www.economic.upit.ro/

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  1. Franck Moraux & O. Renault, 2002. "30 ans de modèles structurels de risque de défaut," Post-Print halshs-00076643, HAL.
  2. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-474, October.
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