Research on the Construction of Risk Early Warning Mechanism in Enterprise Financial Management

In today's context of economic globalisation and fierce market competition, how to quickly detect and eliminate financial risks has become a key issue for enterprises to enhance their core competitiveness and healthy development. Aiming at this problem, this study proposes a design scheme of risk early warning mechanism. Firstly, the collected data are preprocessed. Dealing with missing values, outliers and duplicated data in the data. Second, based on the common financial risk indicators and data preprocessing results, the Z-value model, logistic regression, support vector machine, and artificial neural networks were compared with the model risk analysis results, and the best risk analysis model was selected. Again, an early warning signal analysis strategy was proposed. Subsequently, the prediction accuracy of risk monitoring cost models such as linear regression model, support vector machine, and artificial neural network were compared to complete the selection of risk monitoring cost models. Finally, according to different risk levels, corresponding contingency plans were formulated to complete the design of the risk response layer. The objective of this study is to provide novel insights and methodologies for enterprise financial risk early warning, enhance the efficacy of enterprise financial risk prediction, minimise the probability of enterprise financial risk, and facilitate the sound development of enterprise financing.