Research On Financial Risk Early Warning Of Listed Mechanical Enterprises Based On BP Neural Network

In recent years,China’s market economy and stock market are booming,the number of listed companies is increasing,the competition between different enterprises is becoming increasingly fierce,and the instability of internal and external environment leads to the listed companies in various industries may face financial risks,especially in manufacturing enterprises.The financial risk question which the machinery manufacturing industry enterprise faces is also very prominent,after enters the new economic development stage,the machinery manufacturing industry overall is at the murky condition,each kind of question has limited the machinery manufacturing enterprise’s development,for example the bad account bad account unceasing increase,the stock backlog as well as account receivable soars and so on.Coupled with the global economic and trade friction conflicts,the worldwide market uncertainty,the internal and external environment of the machinery manufacturing enterprises is facing increasing financial risk.Therefore,it is very necessary to construct a monetary early warning model for listed enterprises of machinery manufacturing industry,to predict the financial risks in the process of business operation,and then to take preventive and responsive measure.Firstly,the paper selects the listed mechanical enterprises as the research object,and analyzes the pecuniary risk,financial early warning theory and financial early warning methods.Secondly,the characteristics of machinery enterprises,financial risk types and causes are analyzed.In order to address the problem of lack of financial earlywarning mechanism in the machinery industry,the BP neural network model is used to construct the financial early-warning model of machinery listed companies.Then,in the machinery listed companies,the sample selection,the final selection of 93 companies,using SPSS software for factor analysis of early warning indicators,early warning indicators to maximize the division of the sample interval,BP neural network model of training and testing.Finally,through the case analysis of Thinker Agricultural Machinery Co,Ltd,using the enterprise data to test the model,the results show that the BP neural network model based on mechanical listed companies can accurately prewarn the financial risk of Thinker Agricultural Machinery Co,Ltd,according to the screening of early warning indicators to analyze the financial situation of Thinker Agricultural Machinery Co,Ltd,understand the risk situation of enterprises and put forward the corresponding countermeasures.