Research On Intelligent Monitoring Of Corporate Financial Risk Based On Sustainable Development Perspective

Since the outbreak of epidemic,most companies around the world have fallen into varying degrees of financial distress and encountered financial risks due to various factors.At the same time,people are increasingly aware of the impact of natural disasters and public health events on businesses.In today’s globalized economy,the concept of sustainable green development is gaining attention,and investors are gradually taking into account whether companies have positive sustainability performance when measuring listed companies to make more reasonable investment portfolios.However,corporates need to pay a huge cost in practicing their sustainable performance,which is contrary to their profitability purpose.Exploring the connection between sustainable performance and corporate financial risk has gradually become a hot topic in academia.At present,many domestic and international studies have drawn on ESG ideas to explore the connection between environmental protection,corporate social responsibility,corporate governance and corporate financial risk,but most of them are conducted from a single dimension or perspective,and few articles have been published on the connection between overall sustainable performance and financial risk.Domestic sustainability-related research is relatively late,and the evaluation criteria are not uniform,so more researchers are needed to explore this research gap.In this paper,the 2012-2021 A-share listed companies in Shanghai and Shenzhen are selected as the research sample,firstly,the data of three mainstream ESG rating agencies in China are collected,and the rating index is optimized and revised to construct the rating index;Secondly,the classical Z-Score index is selected as a proxy variable for corporate financial risk,and the relationship between ESG performance and corporate financial risk is explored using a twoway fixed-effects model for individual firms and time,and heterogeneity analysis is conducted based on the nature of ownership and size of firms,and the robustness of the model is tested by adding lagged variables and replacing the explanatory variables.Finally,this paper considers that traditional machine learning algorithms are unable to capture the correlations that exist between firms and enterprises,so graph neural networks are used to predict the future financial risks of firms.This paper constructs a graph neural network for predicting the financial risk of enterprises by obtaining the dynamic association structure between listed enterprises through an explicit and implicit dynamic association deep learning algorithm,capturing the potential connections between enterprises and aggregating the information around enterprises to make a more comprehensive,reasonable and accurate prediction of financial risk.The empirical results found that ESG rating performance has a significant positive impact on corporate financial risk index,i.e.,it significantly reduces corporate financial risk.Improving ESG ratings for enterprises of different ownership nature and size can significantly improve the corporate financial risk index,but the effect of improving the corporate financial risk index from improving ESG ratings for non-state enterprises and small-scale enterprises is more significant compared to state-owned enterprises and large-scale enterprises.When the model is tested for robustness by adding lagged variables and replacing the explanatory variables,the results are still significant.The results obtained using graphical neural networks for predicting the future financial risk of enterprises outperformed those of mainstream machine learning,demonstrating its feasibility in the field of financial risk prediction.From the perspective of sustainable development,this paper combines sustainable development and corporate financial risk,which enriches the relevant research and provides references for governmental part to formulate relevant regulations,regulatory authorities to maintain market order,enterprises themselves to prevent financial risk,and investors to select investment portfolios.