Research on Enterprise Financial Risk Early Warning System Model Based on BP Neural Network

In the era of economic globalization and continuous reform of China’s political, economic, and cultural systems, China’s financial markets have rapidly aligned themselves with the pace of global developments. Financial innovation has emerged as a dominant trend in the current economic and social landscape, meeting the demands of a market-oriented economy’s development. However, this innovation acts as a double-edged sword. On the one hand, it yields economic benefits, but on the other, it introduces potential risks to the global economic environment and disrupts the orderly flow of international financial capital. Furthermore, it exposes global enterprises’ financial capital to a wider array of influencing factors. Recognizing the limitations of discriminant analysis within traditional statistical methods for assessing enterprise finances, this paper breaks free from conventional risk early warning models. It highlights the advantages and untapped potential of neural networks in financial assessment applications. Specifically, it employs an enhanced Back-Propagation (BP) neural network method to construct an early warning system for enterprise financial risks. This approach represents a novel paradigm shift in addressing financial risk in the modern business landscape.