Research On Intellectual Property Pledge Financing Mode And Risk Management

With the integration of the rapid development of science and technology and global economic integration depth,the high-tech SMEs as the core of intellectual property rights is growing as the main driving force leading China economic restructuring and development,plays an important role in stabilizing the economy,optimize the industrial structure.However,the financing difficulties and financing costs of the enterprises have become the major problems that restrict their development.Therefore,it is urgent to ease the plight of enterprise funds.The pledge financing of intellectual property rights is the product of the integration of science and technology and finance.It has been widely promoted and applied in the developed countries of intellectual property rights,and has provided enormous funds for the growth and development of small and medium-sized technology-based enterprises.In recent years,the application of intellectual property rights and the amount of authorization have been greatly developed,and the intellectual property pledge financing has also been generally recognized by enterprises.However,the cautious attitude of banks and guarantee institutions has hindered the progress of financing business.Preventing and reducing risks is the key to opening intellectual property pledge financing business.Domestic scholars have studied the risk of intellectual property pledge financing from different subject perspectives,and have made remarkable achievements.But the pledge financing of intellectual property rights is a complex and dynamic systematic project.It is affected by both macro policy and participation.The existence of risk is the result of many factors.Simply from a point of view of risk,it is difficult to meet the needs of participating in pledge financing business in various ways.So,to identify the risk type,revealed the formation mechanism,assess the static risk before financing,monitor and early-warn the dynamic risk after financing from the systematic perspective is particularly important for reducing the risk of intellectual property pledge financing,promoting the development of pledge financing business and realizing the drive strategy of technological innovation.Based on the above understanding,this paper uses the method of theoretical and empirical analysis,systematically established the pledge of intellectual property financing risk research framework,the main line of the research is "pledge mode—risk factors—the formation mechanism of financing risk — the risk static evaluation before financing—dynamic monitoring and early-warning after financing".The main contents are as follows:Firstly,the paper elaborates the key problem of this research,research methods,technical route and the innovation points,an set up the basic platform of the research,which based on the background and significance of the research and the research status at home and abroad in related areas.The knowledge economy theory,information asymmetry theory,limited rationality theory and cooperative game theory are introduced as the theoretical basis of this study.Secondly,from angle of analyzing intellectual property pledge financing mode risk as the breakthrough point,the paper constructs the intellectual property pledge financing mode based the third party dynamic risk monitoring platform.Comparing and analyzing the domestic and foreign intellectual property rights from 8 dimensions,we summarized the advanced experience of foreign mature IPR financing mode.Combined with the actual situation in our country,we provide the intellectual property pledge financing mode based the third party dynamic risk monitoring platform,which monitors the risk as the core concept,transfer information among the finance enterprises,banks,intermediaries,government and platform participants as a link,shares the risk and income as principle.Thirdly,the formation mechanism of intellectual property pledge financing risk is analyzed.We summed up 2 external factors and 5 internal influencing factors by identifying,screening and analyzing the risk factors in the process of intellectual property pledge financing.The external influence factors include government support policy and industry development prospect,the internal influence factors include the risk factors of the financing enterprises,the banks,the intermediary structure,the third dynamic risk monitoring platform and the risk factors between the participants.The financing risk caused by the influence factor is classified into 5 risk subsystems: government and industry risks,credit risks,intellectual property rights risks,operational risks and relationship risks among participants.Based on system dynamics theory,we analyzed the risk factors and their causal relationship,construct the causality diagram of risk subsystem,construct the causality diagram of intellectual property pledge financing risk according to the interaction among the risk subsystem,and depict the risk transfer path.Above the analysis,this paper uses system theory to reveal the formation mechanism of intellectual property pledge financing risk from three dimensions,which are external risk factors,internal risk factors and the whole system operational risk.The research shows that the internal risk factors are more important than external risk factors,including the credit risk of financing enterprises,the dynamic risk monitoring platform,the intellectual property risk,the qualified approval risk of the monitoring platform and banks,and the relationship risk among the participants.Any subsystem risk factors is activated or enhanced,the effect of the factor will be transferred to the intellectual property pledge financing system through the increased subsystem risk,and the risk of the whole system will be increased.Fourthly,the intellectual property rights pledge financing risk static evaluation is studied quantitatively from the systematic perspective in order to solve the problem of risk evaluation in the choice of pledge financing enterprises.On the basis of the theoretical analysis of intellectual property pledge financing risk,the paper constructs the static evaluation index system of intellectual property pledge financing risk,which includes 38 specific indexes in 16 dimensions.Since there are both quantitative indexes and qualitative indexes in evaluation indexes,it is difficult to evaluate them with an accurate value in qualitative indexes.Therefore,this paper uses the fuzzy advantage of Vague set method and combines TOPSIS multiple attribute decision making method to establish the static evaluation model of intellectual property pledge financing risk to evaluate risk.we selects 5 companies from the intellectual property pledge financing enterprises as the research objects,and transfer the 21 quantitative indexes to the form of Vague sets through other scholars' quantitative index transformation formula,the qualitative indicators are designed to five levels: lower risk,low risk,general,higher risk and high risk according to the impact degree of risk.We invite 10 experts to judge company risk for 17 qualitative indicators.In the statistical evaluation results,the real subordinate function of the Vague set is designed as the result of the judgment of low risk and lower risk,and the result of judging the higher risk and higher risk is designed as the pseudo membership function of the Vague set,the result of judging the general risk is designed as the uncertainty of the Vague set,the judgment result is expressed in the form of Vague set,so the judgment matrix of the Vague set is constructed,and the fitness matrix SM is established,and determine the TOPSIS positive ideal solution VPIS and the negative ideal solution VNIS in form of Vague sets.The weights of each index are evaluated by analytic hierarchy process.The Euclidean distance and relative proximity of different sample firms to positive and negative ideal solutions are calculated,and the risk of different Sample Firms is judged according to the proximity value.At last,the risk of the pledge financing of the company is analyzed according to the industry,the management level,the R & D and the market operation of sample firms.Finally,the Kalman filter is used to monitor and warn the risk after financing.After the granting of loans by banks and other financial institutions,changes in the financial status and operating conditions of the financing enterprises have become the focus of the financing risk.The impact of non-financial information on enterprises will be concentrated through financial indicators,and there will be significant differences in financial indicators between companies with high financial risk and financially healthy companies,the financial risk can be effectively studied whether the financial statements calculated directly through financial statements or the financial indicators indirectly calculated through financial statements.In view of the enterprise financing risk is dynamic and cumulative,using the optimal linear recursive filtering,Kalman filtering,to realize the real-time dynamic monitoring and early-warning through the financial time series data.This paper selects the financial indicators in the static evaluation index system for monitoring and early-warning the risk.88 small and medium enterprises are selected from the wind database.We chose 21 financial ratios from 2013 until 2016 in the annual report and semi-annual reports,including 12936 data for the empirical study.Through the descriptive statistics,correlation analysis,the standard conversion and the principal component analysis,we can know the ratios changing sustainability and cumulative effect.The samples are divided into health enterprises,mild and severe risk enterprises according to both net profit and net operating cash flow.we use the samples data to extract the two-point thresholds of the company's risk transformation from good to bad,from light to heavy.Stochastic filtering model is established,the companies' reported data is input and the companies' real state data is output.In this study,MATLAB program is used.It links the time series update and reported update algorithm,and revise the model parameters to achieve the optimal filtering equation.Input the sample data to the optimal filtering equation,we will get predictions data,compare with the true value and describe the dynamic predictive curve of the risk situation of the company.We also can discriminate the early warning capacities of this model from the fitting accuracy of the predicted value and the true value,recognition accuracy of the companies risk classification.The results show the dynamic early-warning model based on Kalman filter has higher fitting precision,the average error between the predicted and the true values is 8.5%.The ratio is 9.4% that the risk company is judged to be a healthy company wrongly;Conversely,the ratio is 12.5%,the overall recognition accuracy of the model is 89.1%;which shows that the model has a good early-warning function for the dynamic monitoring of the intellectual property pledge financing risk.This paper provides a new angle of view for the study of intellectual property pledge financing risk.As a complex system engineering,the third party dynamic risk monitoring platform not only strengthen the main link among the participation,weak the risks of asymmetric information,and evaluate the intellectual property pledge financing static risk,monitor and early-warn dynamic risk according to a large number of original data collection.Even if the enterprise can not repay the debt,the platform can also transfer the intellectual property operation successfully.The research results can provide important theoretical and practical significance for the SMEs to make use of their abundant intellectual property resources,ease the shortage of funds and promote the rapid promotion of intellectual property pledge financing business.