A New Methodology for Estimating Internal Credit Risk and Bankruptcy Prediction under Basel II Regime

Credit risk estimation and bankruptcy prediction methods have utilized Altman’s Z-score method for the last several years. It is reported in many studies that Z-score is sensitive to changes in accounting figures. Researchers have proposed different variations to conventional Z-score that can improv...

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Bibliographic Details
Published in:Computational economics 2015-06, Vol.46 (1), p.83-102
Main Authors: Naresh Kumar, M., Sree Hari Rao, V.
Format: Article
Language:English
Subjects:
Accounting
Accuracy
Bankruptcy
Behavioral/Experimental Economics
Bias
Computer Appl. in Social and Behavioral Sciences
Credit ratings
Credit risk
Current liabilities
Economic models
Economic statistics
Economic theory
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Equity
International finance
Math Applications in Computer Science
Operations Research/Decision Theory
Ratios
Regulation of financial institutions
Securities markets
Standard scores
Stock exchanges
Studies
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Summary:Credit risk estimation and bankruptcy prediction methods have utilized Altman’s Z-score method for the last several years. It is reported in many studies that Z-score is sensitive to changes in accounting figures. Researchers have proposed different variations to conventional Z-score that can improve the prediction accuracy. In this paper, we develop a new multivariate nonlinear model for computing the Z-score. In addition, we develop a new credit risk index by fitting a Pearson type 3 distribution to the transformed financial ratios. The results of our study have shown that the new Z-score can predict the bankruptcy with an accuracy of 98.6 % as compared to 93.5 % by Altman’s Z-score. Also, the discriminate analysis revealed that the new transformed financial ratios could predict the bankruptcy probability with an accuracy of 93.0 % as compared to 87.4 % using the weights of Altman’s Z-score.
ISSN:0927-7099
1572-9974
DOI:10.1007/s10614-014-9452-9