Spatial Aggregation Analysis and Systemic Risk Prevention of Internet Finance Based on Neural Network Model

Abstract

With the development of science and technology, the application of neural network model is more and more extensive. In order to avoid the outbreak of financial crisis, economists and policy makers around the world pay special attention to the timely warning of financial crisis. If we can make an accurate early warning of the economic crisis, the government and regulatory agencies will have more time to deal with the possible risks and avoid major interference to economic growth. Based on this, this paper studies the spatial aggregation analysis and systemic risk prevention of Internet Finance Based on neural network model. Based on BP neural network, this paper constructs a spatial econometric model by using spatial econometric analysis method, and analyzes the empirical results of financial spatial aggregation. The results show that the Moran’s I value of China’s Internet finance index in December 2019 is 0.372, P value is 0.001, Moran’s I value of Internet payment is 0.395, P value is 0.002, Moran’s I value of Internet monetary fund is 0.357, P value is 0.001, Moran’s I value of Internet investment and financing is 0.324, P value is 0.002, Moran’s I of Internet insurance is 0.313, P value is 0.001. The results show that there is spatial agglomeration in the development of Internet finance in China. In addition, this paper also studies the systemic risk of Internet finance, analyzes its causes and puts forward corresponding preventive measures.