Financial Management Early Warning Model Based on Two-layer Kriging Element Model Algorithm

At present, with the rapid development of the global economy, the changes of national markets are unpredictable, and the enterprises of various countries are also subject to the influence of the global economic environment. Therefore, companies should follow in the footsteps of the global economy and be prepared and take precautions before the crisis. When a corporate financial crisis occurs, business managers have to respond positively to the crisis. However, the major enterprises are not an independent individual, and the decisions made by an enterprise will often affect its associated enterprises. Therefore, whether enterprises can find the financial crisis and can prevent the arrival of the financial crisis, has been widely concerned by the public. Enterprises require stable development, so we must strengthen the prediction, identification and processing capacity of financial risks, which requires the establishment of financial management early warning model. Financial management early warning model appears in the enterprise management, improve the accuracy of the early warning system, can help enterprises to prevent the arrival of risks, enterprise managers can also make the correct decisions. Establishing financial warning model has become a development trend, which can improve the effectiveness of financial warning research. Design a systematic financial early warning index system, and combined with the Kriging meta-model algorithm, build the enterprise financial management early warning model, and use advanced scientific and technological means to avoid financial crisis. The paper uses literature research method and qualitative analysis method, through simulation experiments found that the Kriging model improves the genetically improved neural network model algorithm by 4%, and the discrimination efficiency is greatly improved, which has certain practical significance.