Rural Financial Decision Support System Based on Database and Genetic Algorithm

Abstract

With the development of society and economy, the rural financial institution system mainly includes cooperatives and political and commercial rural financial institutions, and they are supplemented by agricultural insurance, guarantee, securities and other nonfinancial organizations to improve their own functions. Rural credit cooperatives have higher investment and operation risks than other financial institutions. New-type rural financial institutions are more sensitive to the market environment, asset quality and profitability, and risk-taking ability. Internal and external risks continue to accumulate, and their potential is low. These risks pose serious obstacles to the development and growth of financial institutions such as rural banks and microfinance companies, and pose major challenges to the security and stability of rural areas and agriculture. Using database and genetic algorithm to study rural credit risk, profitability, and liquidity, in order to track the impact of each explanatory variable in the system on the explained variable, the impulse response function is used to analyze the impact of nonperforming loan ratio on asset profitability. The data are all close to 0, indicating that the influence between the two is more obvious. The intelligent decision-making system support system evaluates the market risk, credit risk, liquidity risk, and risk management and risk acceptance of rural financial institutions and explores effective countermeasures for their sustainable development.