Statistical methods in credit risk management
Successful banks base their operations on the principles of liquidity, profitability and safety. Therefore, the correct assessment of the ability of a loan applicant to carry out certain obligations is of crucial importance for the functioning of a bank. In the past few decades several credit scor...
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| Format: | Article |
| Language: | English |
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Faculty of Economics and Business in Osijek
2012-12-01
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| Series: | Ekonomski Vjesnik |
| Subjects: | |
| Online Access: | http://hrcak.srce.hr/file/139699 |
| Summary: | Successful banks base their operations on the principles of liquidity, profitability and safety. Therefore,
the correct assessment of the ability of a loan applicant to carry out certain obligations is of crucial
importance for the functioning of a bank. In the past few decades several credit scoring models have
been developed to provide support to credit analysts in the assessment of a loan applicant. This paper
presents three statistical methods that are used for this purpose in the area of credit risk management:
logistical regression, discriminatory analysis and survival analysis. Their implementation in the
banking sector was motivated to a great extent by the development and application of information and
communication technologies. This paper aims to point out the most important theoretical aspects of
these methods, but also to actualise the need for the development and application of the credit scoring
model in Croatian banking practice. |
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| ISSN: | 0353-359X 1847-2206 |