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2005 | nr 52 | 169-189
Tytuł artykułu

Nowoczesne modele zarządzania ryzykiem kredytowym

Warianty tytułu
New Models of Credit Risk Management
Języki publikacji
PL
Abstrakty
W ciągu ostatnich lat największe instytucje finansowe zaczęły wspomagać się w swoich decyzjach, dotyczących pożyczek korporacyjnych modelami pomiaru ryzyka kredytowego. Na taki stan rzeczy wpłynął fakt, że dług korporacyjny charakteryzuje się mniejszymi premiami za ryzyko oraz mniejszą stabilnością niż w przypadku dużych portfeli detalicznych, ze względu na niższy stopień ich dywersyfikacji. Założeniem modeli jest pomoc w kwantyfikowaniu, agregowaniu oraz zarządzaniu ryzykiem kredytowym poprzez określenie prawdopodobieństa wystąpienia trudnych sytuaji dla pojedyńczego kredytobiorcy.(fragment tekstu)
EN
In the past few years, major advances in credit risk analytics have led to the proliferation of a new breed of sophisticated credit portfolio risk models. A number of models have been developed, including both proprietary applications developed for internal use by leading--edge financial institutions, and third party applications intended for sale or distribution as software. These new models allow the user to comprehensively measure and quantify credit risk at both the portfolio and contributory level, which was not possible previously. As such, they have the potential to cause profound changes to the leading business, accelerating the shift to active credit portfolio management, and eventually leading to an "internal models" reform of regulatory credit risk capital guidelines. Models for measuring credit portfolio risk require several input parameters - firstly, to quantify the loss risk from the individual positions and, secondly, to take the pairwise interdependencies, which are determined by joint risk drivers, into account at the portfolio level. Considering the loss that a bank can expect from a typical buy and hold transaction (assumption: no premature disposal is possible or attractive), it is obvious that such a loss is already made up of three uncertain components: Expected Loss = Default Probability • (Outstanding Exposure • (1-Recovery Rate)) Usually estimation of the probability of default is initially based on an individual credit analysis (rating) but can vary considerably over the time horizon of the loan contract. The expected exposure at the time of default (discounted, outstanding interest and repayment) is likewise an uncertain value in the common case of unused lines of credit e.g. Finally, the recovery rate is calculated as a percentage of outstanding nominal exposures and can depend on the future marketability of tangible collateral, hardly predictable work-out costs, etc. Credit-risk-measurement models are using the proliferation of public data and its products, available electronically and updated regularly, to provide a constant flow of information that is quite independent of the accounting-based data that has been the backbone of financial analysis for so many years. No model is ideal. All have individual strengths and weaknesses. But all bring value to the manager whose intent to understand risk and measure it as accurately and as often as possible. (original abstract)
Rocznik
Numer
Strony
169-189
Opis fizyczny
Twórcy
Bibliografia
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  • Gordy M., A Comparative Anatomy of Credit Risk Models, Journal of Banking and Finance 1999, no. 8.
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  • Sandauers A., Metody pomiaru ryzyka kredytowego KMV. VAR, Credit Metrics, LAS, RA-ROC, Credit Risk Plus, Dom Wydawniczy ABC, Krakow 2001.
  • Santamero A.M., Commercial Bank Risk Management: An Analysis of the Process, University of Pennsylvania, Working Papers 1995.
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  • Wilson T.C., Measuring and Managing Credit Portfolio Risk, Unpublished Draft, 1997
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171221951
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