Big Data Governance Research On Lending Risk Of Nongovernment Informal Financial Organization

In the 5th central committee conference of 19th National Congress of Communist Party of China,it is clearly stated that it is necessary to "strengthen the financial risk prevention,early warning,handling,and accountability system,and zero tolerance for violations of laws and regulations","maintain financial security,and hold the bottom line of systemic risks.",which proposed the methods and goals for national financial risk governance in China during "14th-Five-Year Plan" period from macro and micro perspectives.The lending risk of nongovernment informal financial Organization(NIFO)represented by illegal fund and cash loan is a mainly risk governed by local governance,and preventing and controlling the lending risk of NIFO is a meaningful part in the national financial risk governance during "14th-Five-Year Plan" period.In recent years,the Wenzhou’s nongovernment financial crisis and the lending risk of NIFO such as illegal fund driven by the technology have erupted one after another.Local financial governments as Guangzhou have gradually explored the effective governance path of local financial risk driven by big data,and has achieved significant results.However,the lending risk of NIFO change hugely,hidden deeply,which is difficult to capture,and the currently governance methods are still in the exploratory stage,lacking systematic and scientific theoretical thinking.Especially,under the tendency of government governance innovation and reform driven by big data,exploring the big data governance issues on lending risk of NIFO have an important practical value for risk governance model innovation,to precisely and efficiently govern lending risk of NIFO.Therefore,based on the investigation and empirical analysis,this article systematically explores the big data governance issues of lending risk of NIFO,and the potential innovations accordingly are as follows:First,focus on the factors of big data governance of lending risk of NIFO.From micro and macro perspectives,this article identified the factor as risk subject,monitor index of big data governance of lending risk of NIFO,which provides an empirical evidence to scientifically construct the big data governance system of lending risk of NIFO.Second,focus on the monitor and early warning of lending risk of NIFO.Comprehensively using the deep learning method as LSTM,GWO hybrid models,this article believed that the LSTM model has a more precisely accuracy on the early warning of lending risk of NIFO than other models,which can be an efficiently tools used in the risk governance of big data,providing an objective reference for the governance method choosing of big data of lending risk of NIFO.Third,focus on the big data governance system of lending risk of NIFO.From the perspective of duo-government role,data governance,risk identify and early warning,risk decision and disposal,this article constructed a big data governance system of lending risk of NIFO,which enriched and optimized the current governance model of lending risk,to provide an efficiently reference for the illegal risk governance of local government.Based on survey analysis,empirical analysis and case analysis,conclusions are concluded as follows:First,the nongovernment informal financial organization is significantly non-regulatory,which is clearly different from folk financial organization and formal financial organizations.Second,from micro perspective,variables as business and capital turnover expenditures,gender,and monthly average income have a positive impact on default risk of lending demand,while variables as house purchasing,medical expenditure,and credit education level have a negative impact.There is an obvious mediation effect on default risk of lending demand,and variables as income and credit education level plays a part of intermediary effect.Variables as relatives or friends,latest investment amount,loan service evaluation,and understanding degree of loan fund disposal have a significant negative impact on default risk of lending supplier,and variable of the recently loan term has a positive impact.There is an obvious mediation effect on default risk of lending supply,and variables as lending information transparency plays a part of intermediary effect.Therefore,it should monitor the risk subject as NIFO,strengthen the monitor on index as default and lending interest rate,and construct a duo governance system.Third,spatially,there are obviously spatial accumulation and spillover effects of lending risk of NIFO,with a steadily downward tendency,and the risk hot spots are located in the in the eastern coastal areas and central regions.Variables as accounts receivable by private enterprises,growth rate of investment in fixed assets and proportion of real estate investment have a significantly positive impact on default risk of NIFO of lending supplier,while the proportion of real economy has a significantly negative impact.The spatial lagged coefficients of variables as quadratic of expenditure gap of local government and accounts receivable of private enterprises,proportion of the real economy,and the non-performing loan ratio are all positive,and there is a stronger regional spillover effect.Therefore,it should monitor the risk subject of enterprise and government,and strengthen monitoring on macro index as local fiscal and the growth rate of real economy,and enhance the regional correlated governance.Fourth,using the LSTM and GWO hybrid models to explore the accuracy and robustness of machine lending method on folk lending risk prediction.And the empirical results show that the LSTM hybrid models can effectively predict the lending risk of NIFO,with robustness.Therefore,it should enhance the implication of machine learning on the risk monitor and early warning of lending risk of NIFO.Fifth,there are five characteristics of big data governance of local financial risk,as big data governance according to dynamic closed circle process,data governance on big data,duo risk identification,artificial intelligence of risk monitoring and early warning,and correlated collaboration of risk decision and disposal.Based on above,this article constructed a big data governance system of lending risk of NIFO from four aspects as duo-government role,data governance,risk identification and early warning,and risk multilevel decision and disposal.At last,policy implication has taken from big data guarantee mechanism and technological innovation,data-smart decision,and other dimensions to provide governance reference for local financial risk prevention and control.