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2018 | 28 | nr 4 | 99--106
Tytuł artykułu

Credit Risk Management in Finance : a Review of Various Approaches

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Classification of customers of banks and financial institutions is an important task in today's business world. Reducing the number of loans granted to companies of questionable credibility can positively influence banks' performance. The appropriate measurement of potential bankruptcy or probability of default is another step in credit risk management. Among the most commonly used methods, we can enumerate discriminant analysis models, scoring methods, decision trees, logit and probit regression, neural networks, probability of default models, standard models, reduced models, etc. This paper investigates the use of various methods used in the initial step of credit risk management and corresponding decision process. Their potential advantages and drawbacks from the point of view of the principles for the management of credit risk are presented. A comparison of their usability and accuracy is also made. (original abstract)
Rocznik
Tom
28
Numer
Strony
99--106
Opis fizyczny
Twórcy
  • University of Economics and Business, Poznań, Poland
Bibliografia
  • [1] ALTMAN E., RESTI A., SIRONI A., Default Recovery Rates in Credit Risk Modelling: A Review of the Literature and Empirical Evidence, Economic Notes by Banca Monte dei Paschi di Siena SpA, 2004, 33 (2).
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  • [20] WÓJCICKA A., Sensitivity of the MKMV model to the method of estimating the growth rate of the value of assets, [In:] Taxonomy 15. Classification and data analysis - theory and applications, K. Jajuga, M. Walesiak (Eds.), Wrocław University of Economics, Wrocław 2008, No. 7 (1207), 182-189.
  • [21] WÓJCIK-MAZUR A., Managing credit risk in commercial banks, Czestochowa University of Technology, ser. Monograpphies, No. 143, Częstochowa 2008 (in Polish).
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171543116

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