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Research On Logistics Financial Risk Early Warning System Model Based On FA-BPNN

Posted on:2019-02-08Degree:MasterType:Thesis
Country:ChinaCandidate:H W ShenFull Text:PDF
GTID:2429330548969381Subject:Engineering
Abstract/Summary:PDF Full Text Request
With the development of China's financial market,the field of logistics service is more perfect and service standards are constantly moving towards integration and specialization,which combined with the requirements of the era of big data.Under the background of continuous compression of traditional logistics service mode,logistics enterprises actively respond to national policies,innovate and vigorously develop logistics financial services business.One of the main sources of profit is the flourishing development of logistics and finance for modern logistics enterprises.For financial institutions,the participation of logistics enterprises can reduce financial risks and concentrate their efforts on expanding business.For the financing enterprises,it is more convenient to get the help of funds in order to realize the common profit of the three party.Therefore,the integration of logistics and finance has become a common concern of the logistics industry and the financial industry.It is also a hot topic of research in recent years.Until now,logistics finance business has been dominated by financial institutions such as banks and gradually changed to be dominated by logistics enterprises.So,the financial risks faced by logistics enterprises as third-party cooperation enterprises are increasing.However,due to the imperfect development of logistics finance in China,the research on financial risk based on the third-party logistics enterprises are limited to the establishment of index system,and there is no further research and analysis.Therefore,the construction of an effective logistics financial risk early warning model is of guiding significance for the actual operation of logistics enterprises,and can also enrich the research theory in this field.Based on the related theories of logistics and financial risks,this paper is based on the research results of scholars at home and abroad.First of all,this paper analyzes the modern logistics financial business development mode,mainly based on inventory pledge financial mode and trade contract based financial mode,including operational practices including warehouse receipt mode,financing warehouse,confirming warehouse,e-commerce warehouse,order mode,etc.Secondly,according to these logistics financial models,this paper expounds the logistics financial participation mode,and the logistics financial risks faced by them,identifies risks,and constructs evaluation index system of logistics financial risks.Then the factor analysis method is used to further deal with the index data,and the concrete methods and steps of constructing the early warning model are expounded with the neural network algorithm.Finally,a case analysis of logistics enterprise A is carried out,and the FA-BPNN method is used to construct the early warning model of logistics financial risk.The paper proposes the response measures combining with the results of early warning.The results show that the model has practical guiding significance.The innovation points of this paper are shown in the following points.This paper summarizes the logistics finance business mode of modern logistics enterprises,classifies and collates them.On this basis,it puts forward the index system of early warning model combined with the form of logistics enterprises participation.From the perspective of third party logistics enterprises,and referring to the establishment method of enterprise financial early warning model,this paper expounds the specific steps of building logistics financial risk early warning model based on FA-BPNN.Finally,on the basis of previous studies,combined with the actual financial business development of logistics enterprises A,we get data,build early warning model and verify the model,and put forward the corresponding risk management measures.
Keywords/Search Tags:Logistics Finance, Early Warning Model, Factor Analysis Method, Neural Network Algorithm
PDF Full Text Request
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