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Research On Credit Risk Evaluation For Small And Medium Commercial Bank

Posted on:2015-02-08Degree:DoctorType:Dissertation
Country:ChinaCandidate:P LvFull Text:PDF
GTID:1109330467485973Subject:Economic Systems Analysis and Management
Abstract/Summary:PDF Full Text Request
Small and medium commercial banks’credit risk evaluation is the assessment of their overall financial capability in paying its financial obligations. Also, This evaluation based on a comprehensive analysis of a bank’s credit risk conditions is the comprehensive evaluation of the risks faced by them such as external risk, asset quality, industry risk, market risk, interest rate risk, capital adequacy and liquidity risk and profit situation. Obtaining credit rating which is in line with international practice has become an important strategy and means in establishing a healthy image, expanding their business, reducing transaction costs and improving market competitiveness.This paper consists of six chapters. Chapter one analyzes the research background, methods, technical route and content. Chapter two is the discussion of characteristics of credit risk and influencing factors of small and medium commercial banks. Chapter three is about the foundation of small and medium commercial banks’evaluation index system. Chapter four establishes evaluation model based on the ideal interval of TOPSIS. Chapter five selects14small and medium commercial banks, does empirical analysis and make the foundation of credit evaluation criteria. The sixth chapter is the conclusion and outlook. The main framework is as follows:(1) Construction of small and medium commercial banks’credit evaluation system which includes internal and external influencing factors. Multiple correlation coefficient and correlation coefficients of quantitative indicators under the same criteria layer are calculated in order to study the correlation of one indicator and the overall indicators, as well as the correlation between the indicators. Indicators which simultaneously reach multiple correlation coefficient and the correlation coefficient thresholds are deleted. Also, indicators which reflect duplicate information are removed to ensure the integrity of the index system information after screening. Then expert knowledge and experience are used to add and delete indicators after objective screening methods, thereby establishing a small and medium commercial bank credit risk evaluation index system which includes16internal and8external factors evaluation indicators. This system fully reflects the bank’s own credit risk status and its external operating environment, solving unreasonable problem that is the existing evaluation systems just focus on operating indicators of the banks themselves, ignore impacts on its credit risk by the geographical characteristics of their business environment.(2) Establishment of TOPSIS evaluation model base on ideal range. The3a principle is used to build the ideal range of positive and negative indicators which replaces the range based on maximum and minimum values. Individual differences larger evaluation data and singular value index data are interval smoothing to effectively eliminate the influence of outliers on the results of the evaluation indicators, improving TOPSIS evaluation method and establishing evaluation model based on a combination of interval TOPSIS. Thereby the problem that the singular value index data result in evaluation model not usable is solved, which ensures the reasonableness of the evaluation results and improves the credibility of evaluation results.(3) Introduction of combination weighting method based on Theil coefficient. Combination optimization evaluation model which includes AHP, coefficient of variation, mean-variance, entropy method is built by the use of Theil coefficient. We use Theil coefficient to determine the weighting coefficients of single evaluation method, and then use weighting coefficients to combine the evaluation index weights obtained by a single evaluation method and last obtain the combined evaluation index Theil coefficient weight. Integrated combination weight takes advantages of subjective and objective methods of weighting, fully reflects experience and expertise and true information of index data, solves strong subjectivity and arbitrariness of a single subjective weighting method which lead to two defects, the existence of consistency and subjective, of evaluation results, as well as solves the problem that the evaluation results of objective weighting method are not comparable, because this method relies heavily on the sample data.(4) Small and medium commercial banks’classification criteria of evaluation results based on empirical study.We test and verify the effectiveness of TOPSIS evaluation model base on ideal range and combination weighting based on Theil coefficient through the use of empirical study and Spearman rank correlation coefficient. We also introduce interval length and the jump magnitude to the reference level of different levels on the main scale, then expand in both directions up and down by a certain growth (or deceleration) which use the baseline level as the centers. We base the degree of dispersion of the distribution of the evaluation object-level to modest correct level changes in speed, so a mapping between the probability of default and credit risk evaluation closeness is built. Thereby a relatively objective classificationcriteriaof small and commercial banks’ credit risk assessment is developed.
Keywords/Search Tags:Credit Risk, Credit Risk Evaluation, Small and Medium Commercial Banks, Multi-attribute TOPSIS Evaluation Method, Combination Weighting
PDF Full Text Request
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