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Research on Chinese Farmers’Credit Rating in Micro-Finance

Author: WangYing
Tutor: DaiLiang
School: Guizhou College of Finance and Economics
Course: Finance
Keywords: Micro-finance Farmers’credit risk BP model Credit rating
CLC: F832.4
Type: Master's thesis
Year: 2011
Downloads: 155
Quote: 0
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Abstract


Microfinance institutions appears timely fully play its positive role in rural finance. However there is a special nature of credit risk for farmers in China. The farmers’credit evaluation criteria are not standardized, the rating process is lack of scientific method, for various reasons led to the credit rating agency process has blindness and randomness. Since a lot of problem in the work of credit ratings appeared, cause the credit institutions can not recover the funds in time and even cause serious damage. So, how to improve the micro-credit institutions’accuracy of credit rating and achieve healthy and sustainable development of credit institutions, is a urgent requirements.This research based on a theoretical analysis and empirical analysis of the farmers’ credit risk. Through the introduction and comparing of different credit rating methods, we find that we should use more scientific and rational credit rating methods. Such as computer science neural network BP model. And we selected 16 indicators, including farmers’solvency, business conditions, credit conditions, soft assets and so on to reseach.By the research on some parts of Guizhou Province of China micro-credit farmers’credit data, a total of 334 farmers selected to be a sample for modeling research. And we selected 50 farmers and 154 non-breaching farmers as training samples; the remaining 130 farmers’data to be the test samples. By the use of MATLAB 7 software analysis, empirical results show that BP model in the credit grading process got the high accuracy up to 94.5%.Of this analysis we reached the following conclusions:the physical features of farmers’solvency, business conditions, creditconditions, soft assets can reflect the level of farmers’credit conditions; BP neural network is feasible and effective to assess and control micro-credit farmers’credit risk; Micro-credit institutions should considering the level of farmers’moral conditions when the assess the level of farmers’ credit; We must strengthen the supervision of the central bank and let them play a active role in the micro-credit operations.And we need to improve relevant laws and regulations to establish an effective incentive mechanism for micro-credit.

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CLC: > Economic > Fiscal, monetary > Finance, banking > China's financial,banking > Credit
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