Research On Financial Crisis Prediction Of Driven By Big Data Technology

Manufacturing is an important foundation of the national economy and plays an important role in the overall economic operation.As the most important component of the secondary industry,it will also have an important impact on the tertiary industry.Therefore,once the manufacturing industry fluctuates,there will be serious spillover,disrupting the smooth operation of the national economy and even the whole society.With the impact of the Sino-US trade war,the new crown epidemic and the country’s economic transformation,the development of the manufacturing industry is facing multiple problems.At the same time,with the characteristics of heavy assets,high entry barriers and fierce market competition of manufacturing enterprises,the risk of financial crisis of manufacturing enterprises,especially machinery manufacturing enterprises,is getting higher and higher.Therefore,it is of great significance to do a good job in early warning of financial crisis in the machinery manufacturing industry.This not only helps enterprises prevent and deal with financial crises,but also intercepts the spillover of financial crises to upstream and downstream enterprises;It is more conducive to the smooth and healthy operation of the machinery manufacturing industry and provides a certain guarantee for the healthy and stable development of the national economy.The emergence of big data technology allows enterprises to mine and process enterprise-related text information in a wider range,lower cost,and higher efficiency.It has become a new method of early warning of financial crises,compared to using only internal financial data to predict the probability of a financial crisis of enterprises.The use of big data collection data can avoid the shortcomings of excessive subjectivity,time lag,and enterprise fraud in the past financial data,and fully consider the possibility of corporate financial crisis from two perspectives: internal and external perspectives.These advantages make it more necessary to build a financial crisis early warning model driven by big data technology.In this study,literature analysis and mathematical statistical analysis were used to extensively collect sample data of machinery manufacturing industry to construct a financial crisis early warning model driven by big data technology.Then,taking Z,a typical enterprise in the machinery manufacturing industry,as an example,the case analysis method and combing statistical analysis method are used to predict whether the financial crisis of enterprise Z will occur.This not only helps Z enterprises solve the existing financial crisis early warning problems,but also provides enlightenment for the financial crisis early warning work of other machinery manufacturing industries.Starting from the construction of a financial crisis early warning model,this study first sorts out the literature on the definition of financial crisis,the early warning method of financial crisis,and the early warning index of financial crisis.Secondly,this study takes 99 typical enterprises in the machinery manufacturing industry as the research sample,and uses public financial data to construct a financial crisis early warning model with 4 dimensions and 17 indicators based on the internal perspective of the enterprise.Third,this study uses big data crawler technology to crawl text information related to enterprises.Combined with the original financial data,based on the internal and external perspectives of the enterprise,the news media attention,news media emotional tendency,small and medium-sized investor attention and small and medium-sized investor emotional tendency mined by using big data technology are added to the original analysis model,and a financial crisis early warning model driven by big data technology is constructed.Then,this study uses selected sample analysis to evident the advantages this crisis early warning models,and concludes the final conclusion.Finally,this study takes enterprise Z as a case study,deeply analyzes the relevant financial data indicators and text information indicators,and uses the constructed financial crisis early warning model to predict whether enterprise Z will have a financial crisis.This study concludes that first,the text information data related to the enterprise means that the attitude and investment willingness of investors to the enterprise can reflect the financial status of the enterprise to a certain extent.The emergence of big data technology can make enterprises monitor these text information data more efficiently and conveniently,and provide help for early warning of corporate financial crisis.Second,the financial crisis early warning model driven by big data technology has higher prediction accuracy,which can more comprehensively analyze the operation status of enterprises and analyze the current problems of enterprises based on the internal and external perspectives of enterprises.Third,according to the results of the financial crisis early warning model,enterprise Z will not have a financial crisis.As a large state-owned enterprise,Enterprise Z has always adopted a sound business strategy,so it is unlikely that it will have a financial crisis.However,according to the new indicators,it can prompt the existing financial risks from multiple perspectives,so as to better prevent the occurrence of financial crises.Based on the above conclusions,this study believes that the early warning indicators of financial crisis driven by big data are of great significance to enterprise management,stakeholders and regulators.Compared with the lagging and one-sided nature of financial data,combined with the financial crisis early warning model driven by big data technology,it can more intuitively reflect the financial status of the enterprise from multiple dimensions,while the management,stakeholders and regulatory authorities of the enterprise take appropriate measures in a timely manner to deal with potential crises.Therefore,it is recommended that when enterprises use big data-driven non-financial data financial crisis early warning indicators,they should establish a complete management system and ensure the accuracy and reliability of the indicators.