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Li, Jialu (2014) Credit Risk Measurement and Management of the Commercial Banks. [Dissertation (University of Nottingham only)] (Unpublished)

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Abstract

Credit risk is always the major risk that commercial banks face in China. Currently, for the Chinese domestic situation, the Chinese credit rating system is still far from the advanced method. The credit risk management level is relatively lagged behind. Therefore, if Chinese commercial banks want to improve themselves and become more competitive in the international environment, they need to develop advanced internal models that are suitable for them and construct a credit risk management system that makes banks scientifically measure the risks and manage them. More than that, a new method could help them to lower costs and ultimately allocate the rare capital reasonably.

This study which is oriented to the new Basel Accord is conducting research on how Chinese commercial banks optimize credit risk management with the internal rating method. First of all, this study will comprehensively introduce the global and Chinese status of credit risk management. In the next section, the definition and characteristics of credit risk, the meaning of credit risk management and the content of Basel Accord will be illustrated. In the third section, the contemporary internal credit risk method will be brought up, as well as analysing and determining the suitable one for China practice. The fourth part will introduce the empirical study based on the selected model. And the last part will describe the findings and giving recommendations and conclusions.

This study adopts both qualitative and quantitative methods using theoretical analysis and empirical analysis of credit risk measurement models. Firstly, the relative theories are demonstrated. These are the content of Basel Accord, and the credit risk measurement models. Then, in the empirical part, the study uses data from Shanghai and Shenzhen Stock markets from the 1st January of 2013 to the 31st December of 2013, of 10 ST companies and 10 Non-ST companies. With the calculation of the KMV model, the distance to default will be calculated. Through the comparing of the results, it can be proved that the KMV model could accurately estimate the credit risk of listed companies.

Item Type:	Dissertation (University of Nottingham only)
Depositing User:	EP, Services
Date Deposited:	12 Nov 2014 09:58
Last Modified:	19 Oct 2017 14:00
URI:	https://eprints.nottingham.ac.uk/id/eprint/27392

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