Study On The Rural Financial Operating Risk Early Warning Model Based On Bp Neural Network

In recent years, China's rural financial system reform has made considerable progress. Rural finance has played an important role in promoting National economy, especially the rural economy. However, the overall risk of rural finance in particular operating risk is still serious, and becomes a major obstacle to the new rural construction.The dissertation based on financial risk management theory and evaluation theory and practice of rural financial operations, integrated use of systems analysis, causal analysis, empirical analysis and model analysis method, based on China's rural financial system in depth understanding of operating risks, in sum, summarize, compare and reference index system of monitoring domestic and foreign financial institutions based on research to detect the risk indicators of rural financial management system and early warning. BP neural network is applied to rural financial risks early warning system, and then, the dissertation designs the rural financial operating risk indicators in early warning system and the corresponding warning model. The index system contains five major categories and 21 secondary indicators such as capital risk, credit risk, liquidity risk, income risk and interest rate risk. The results of this dissertation is of great importance to further improve the financial institutions, especially of rural financial institutions operational risk monitoring index system, the basic theory of extensive early warning of financial risks, improve rural financial institutions in risk prevention and management to resolve the efficiency of the new period of socialist construction to ensure that rural financial institutions sound and rapid development, has important theoretical value and practical significance.