Risk Warning Method of Cross-Border Flow of International Business Management Data Based on Integrated Classification Algorithm

The economic and social development in the digital era has put forward new requirements for the cross-border flow of financial data. Financial data are an important carrier of financial information. Due to the sensitivity of financial data, its cross-border flow involves citizens’ personal privacy, the interests of financial institutions and even national financial security. In practice, if there is no effective regulation on the cross-border flow of financial data, it will not only be difficult to explore the potential value of financial data, but also lead to various risks. At present, the United States and Europe adopt different regulatory models for the cross-border flow of financial data. In view of the problems existing in the supervision of cross-border capital flow in our country, this paper puts forward some policy suggestions for improving the existing cross-border capital flow monitoring system in our country. The system takes main supervision and off-site monitoring as the two main lines, sets up the framework of China’s cross-border capital flow monitoring institutions and off-site monitoring content framework, and constructs China’s cross-border capital flow monitoring index system on the basis of learning from international and domestic experience. The results show that cross-border capital flow has a significant effect on bank risk-taking. Considering the heterogeneity of cross-border capital, it is found that capital outflow and portfolio investment have a greater impact on bank risk-taking. A good economic development environment will not only bring profits to banks but also reduce their default risk.