Research on Modeling and Efficiency Enhancement of Complex Corporate Financial Networks Based on Topological Computing Optimization

With economic globalization and the increasing complexity of inter-enterprise business linkages, corporate financial systems have gradually taken on the characteristics of complex networks.This paper firstly gives an overview of the complex network and introduces its basic topological properties, such as clustering coefficient and path length.After that, through the principal component analysis method, the enterprise financial risk early warning indicators are identified, and the key indicators are screened to improve the early warning accuracy.Based on these properties, the financial risk conduction network model of complex enterprises is constructed, the characteristics of the network are analyzed, including network density, centrality distribution, etc., and the effect of financial efficiency enhancement of complex enterprises under the optimization of topology computation is verified in real cases.The results show that most of the financial risk indicators of enterprises have strong correlation, and the degree of centrality of 9 indicators such as "gearing ratio and quick ratio" is more than 50%.In addition, the indicators of "current asset turnover ratio, interest coverage multiple, net profit growth rate" can play the role of intermediary and bridge, and the risk transmission effect among the indicators is high.The threshold value of 0.65 is the watershed of the changes in the financial structure of enterprises, and most of the financial risks in the network have a high degree of similarity in the financial structure when the degree value is 70, and it is negatively correlated with the coefficient of agglomeration, and the coefficient of agglomeration decreases with the increase in the intensity of the points.