- Author
- Popławska Małgorzata (Szkoła Główna Handlowa w Warszawie)
- Title
- Credit Risk Analysis Using Failure Time Models
- Source
- Roczniki Kolegium Analiz Ekonomicznych / Szkoła Główna Handlowa, 2007, nr 17, s. 203-224, rys., tab., bibliogr 14 poz.
- Issue title
- Discovering patterns in economic data
- Keyword
- Instytucje kredytowe, Ryzyko kredytowe, Zarządzanie kredytem, Uwarunkowania mikroekonomiczne
Credit institution, Credit risk, Credit management, Microeconomic conditions - Note
- summ.
- Abstract
- Credit granting institutions have to face the risk that some amount of money that has been lent will not be repaid. Therefore banks and other lending institutions are concerned with the issue of measuring the risk of each credit default, which is needed to accept or reject credit applications. The aim of this paper is to present an approach for classifying applicants, based on duration data - survival analysis. Including an extra dimension - time - in the analysis allows the lending institution to take into account the profitability of a loan. Moreover, failure models give an opportunity to include in the model time-varying covariates - regressors that change in time of the repayment. They make it possible to use in the estimation data about the credits that are still being repayed - censored durations. This method is also a useful tool to predict the influence of the particular characteristics on the probability and the expected time of exit to different kinds of states - complete repayment on time, default but also e.g. an early repayment. (original abstract)
- Accessibility
- The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
The Main Library of Poznań University of Economics and Business
The Main Library of the Wroclaw University of Economics - Bibliography
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- Rosenberg E., Gleit A. [1994], Quantitative Methods in Credit Management: A Survey, The Journal of the Operations Research, Vol. 42, No. 4., pp. 589-613.
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- http://ftp.ics.uci.edu/pub/machine-leaming-databases/statlog/german
- http://www.r-project.org
- Cited by
- ISSN
- 1232-4671
- Language
- eng