The Study On Financial Performance Evaluation Of Rural Small And Medium Financial Institutians Based On Bp Neural Network

At present, China’s rural small and medium-sized financial institutions performance evaluation research is still in the initial stage of exploration. Many research draw lessons from foreign commercial banks or microfinance institutions evaluation system, even have no recognized specifically for small and medium-sized financial institutions of China’s performance evaluation index system. And common financial performance evaluation methods have some defects, so this paper hope to do a bit of improvement to rural small and medium-sized financial institutions performance evaluation system. Trying to base on the study of rural small and medium-sized financial institutions performance evaluation method, with the special of China’s rural small and medium-sized financial institutions, give a set of suitable for the characteristics and nature of financial performance evaluation method----BP neural network. The article is first try to combination the financial performance evaluation with BP neural network method analysis of rural small and medium-sized financial institutions operating performance. Because BP neural network have adaptive, self-learning, self-organization characteristics, it can avoid human factors and fuzzy random, and it’s intelligent algorithm can get a reasonable evaluation result.So, the operating performance of rural small and medium financial institutions is high or low, and how to evaluate is the purpose of this study. First, the paper gives a clear perspective of the premise on the financial performance evaluation, understanding of domestic and foreign issues on the development process and in-depth study of theory, and combined with the nature and characteristics of China’s rural small and medium financial institutions, established rural small and medium financial institutions financial performance evaluation index system. In the choice of evaluation methods, by the study review and comparative analysis of a variety of performance evaluation methods, choose to use BP neural network as the article’s financial performance evaluation method. And reflected the innovative and superiority in the use of BP neural network to financial performance evaluation. Second, give an empirical analysis on the basis of evaluation model, by the training the15rural small and medium-sized financial institutions of2009sample data, finally can simulate2010sample data and according to the results to the5sample units rank. Last, this paper sum up the work, and given the further research prospect and suggestions. It is divided into five parts of a comprehensive system to conduct in-depth research.