Financial Distress Prediction of Small and Medium- Sized Enterprises Based on Artificial Intelligence Technology

In order to further improve the financial management quality of small and medium-sized enterprises, provide scientific and efficient financial information support for enterprise operation decisions and minimize the probability of enterprises falling into financial difficulties and crises caused by factors such as increased economic uncertainty, a financial distress and crisis management method based on machine learning algorithm is proposed with artificial intelligence technology supported. Empirical research was conducted on smes financial distress, with the help of random forest and other four machine learning models to manage financial distress and crisis. The experimental results show that the prediction accuracy of LR model is improved to 0.9061, SVC model to 0.9049, NB model to 0.8720. The result finding that the financial distress and crisis management method proposed in this article based on machine learning algorithms is effective, the accuracy of financial management and forecast can be effectively improved by controlling the variables of macro factors.