Non-retail Internal Rating Model Of Rural Commercial Bank

Bank as financial intermediaries plays a crucial role in the real economy, the bank’s operation is based on credit, that leading to a high risk of their own innate qualities. How to effectively prevent and control the risks faced by banks has been an issue of concern governments and academics. External regulation was supposed to be an effective measure, however, rely solely on external regulation will result in asymmetric information and moral hazard problems. In view of this, it comes the idea that transition from external regulation to a combination of inside and outside. To encourage bank build risk prevention tools and techniques inside. And give some incentives on capital adequacy requirements for that. This is the idea of the Basel II regulatory series of documents. Credit risk is the main risk faced by banks. Using the IRB approach for credit risk measurement and effective prevention is the core content of the Basel Capital Accord. Commercial banks should establish a scientific assessment of the law according to their credit risk measurement.In this paper, using the building of non-retail internal rating model as the starting point, from the perspective of regulation, the establishment of non-retail internal rating through standardized methods model is discussed through.First part is about literature review of non-retail internal rating model establishment, history of the internal rating model can be divided into four main stages:expert judgment stage, scoring card stage, statistical models and non-parametric model stage. Respectively, the advantages and disadvantages of each method were analyzed. Then the theories of rural commercial bank’s non-retail internal rating modeling methods are reviewed, including how other rural businesses management of credit risk in the world.The theory of the rural commercial banks non-retail model establishment is also discussed in the third chapter, the core content of the third chapter is the specific developed methods and processes of scorecard. The main indicators are selected by experts scoring. After the risk factors are selected, using Analytic Hierarchy Process (AHP) decides the weighing of each factor. There are three major steps, first to build analytic hierarchy structure model, Then build the comparison matrices of quantitative and qualitative factors. The final step is to calculate the weights. The maximum eigenvalue eigenvector’s corresponding Unit vector of Judgment matrix is the level of importance weight relative to the level of a certain value factors. Finally, use the cluster analysis to divide the quantitative indicators. Cluster analysis is to classify the object and to ascertain the share weights of individuals in the population. The basic idea is to define the distance among the samples, the similar samples were classified as a class, until the distance between all classes meet certain conditions. Cluster analysis method for quantitative indicators segmented (default number is5) and the cluster has been known for a number of cluster analysis is fast clustering method, which has fast processing speed. It includes two steps, first select clustering points with fast clustering point selection, the second step is to calculate. After Calculation work is done. Banking sector, the risk department, approving departments and other relevant departments would discuss the credit scoring model for final draft. The final draft needs to fine-tune based on actual business to determine the scoring model.Chapter four is about empirical analysis of bank C non-retail internal rating model building According to the preceding theory. The entire development process is discussed, including the open division rules, the specific definition of default, specific programs and rules for data collection and cleaning. And the specific process of index selection, weight division, quantitative data segments and so on. The final Industrial enterprises score card is given. Finally,100samples are using for verification for each card.The last part is suggestions about how to build non-retail internal rating modeling of rural commercial banks. It firstly needs to start from the data and systems, build up the foundation internal rating approach. Secondly, it is need for training related professionals to develop relevant modeling techniques. To build risk management culture, that is a major difficulty of building up internal rating approach according to the surveys. Finally, it is about the organizational structure and institutional policy, which is the emphasis part of the assessment standards of regulatory compliance.the internal rating organization should be melted into the overall risk management framework. be sure to avoid post responsibility is not clear or does not have a relevant job-related duties.