Financial data processing and forecasting model analysis based on neural network

Abstract

Financial data is the key to the survival of an enterprise. The analysis of these financial data can not only see the company's own competitive advantages, but also can see the position of the company in the same industry, which can make it easier for the company to formulate financial plans. Improve financial status, improve economic efficiency, and achieve sustainable development of enterprises. This paper constructs an evaluation index system of a company's financial risk from four aspects: solvency, operating ability, profitability and development ability, and establishes the entropy weight TOPSIS method and the SOM neural network financial risk evaluation model through the neural network model. It solves the disadvantage that the weight of the existing AHP and fuzzy evaluation theory is difficult to determine, which leads to the low accuracy of the evaluation result. At the same time, the financial risk evaluation score is calculated on the basis of systematic theoretical research and empirical analysis, which makes the evaluation and calculation of financial risk more scientific and effective.