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:: year 8, Issue 24 (Summer 2015) ::
JMBR 2015, 8(24): 223-250 Back to browse issues page
Estimating Probability of Default for Individual Obligors Based On Basel II
Mohammad Omidinezhad *
Abstract:   (1966 Views)

Probability of clients' default is the most focal parameter in the credit risk Evaluation based on Basel II Accord. In this research, in order to estimate the probability of default, first, a scoring model applying the Logit Regression Technique using the 1343 clients' personal data, credit history, employment information in one of the country's private banks within 1391-1392 was estimated. Through this study, the clients' credit history was identified as the most important factor influencing the probability of default. The statistic ROC (Receiver Operating Characteristic) of the Model reflected 71.1% implying its high discriminant power. Cluster analysis, using K-means Algorithm, of the scoring estimates of the model lead to 7 rating classes. Next, applying historical default frequency approach, the probability of the default associated with each rating class was estimated. Finally, through the calibration test, the accuracy of the probability of default was confirmed for a sample of 327 credit profiles in 1393.  Undoubtedly, compliance with the international agreements on the banking area is inevitable.

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Type of Study: Empirical Study | Subject: Financial Institutions and Services (G2)
Received: 2015/12/31 | Accepted: 2016/08/29 | Published: 2016/08/29

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
year 8, Issue 24 (Summer 2015) Back to browse issues page
فصلنامه پژوهش‌های پولی-بانکی Journal of Monetary & Banking Research
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