Information Features,Risk Recognition And Investors'Concern Under Financial Technology

Focusing on the investment side,the development of financial technology shoulders the "popular reputation" of reducing information asymmetry and reducing investment risks of investors.However,in practice,the tragedies of unlicensed online lending platforms and traditional financial institutions' wealth management products exploding,causing investors to lose their money,are still frequently staged,and this seems to indicate that it is difficult for emerging financial technology to break through the bottleneck of services.Limited to technical complexity,information fragmentation,and investors' cognitive biases,investors still cannot reasonably "recognize" product information that characterizes investment risks,resulting in serious investment decision-making errors.If things go on like this,it will seriously affect my country's financial performance.Stability and development.In view of this,in accordance with the requirements of the Central Economic Work Conference to "prevent risks",this paper is based on the current financial technology perspective,using document research and evolutionary algorithms,from three levels of underlying asset feature information,derivative product feature information,and institutional platform feature information Comprehensively examine the impact of different information characteristics on investor attention and risk identification,and the empirical logic and conclusions are as follows:First of all,through the current situation and theoretical analysis,the following conclusions are drawn:First,through continuous product innovation and the use of new technological means,online lending institutions are "information intermediaries" in legal form,but "information intermediaries" in terms of business models."Like securitization"operation,but the operation is essentially a "credit intermediary".Under the background that the new asset management significance to study their information risk identification and investor attention in different dimensions.Second,according to the theory of information overload in the context of big data,investors are unable to process all the information and make effective decisions.In addition to fully disclosing information to investors,operating institutions should disclose information appropriately according to the degree of importance of the information.Third,through further analysis of financial promotion and investor perception bias,it is necessary to pay attention to the fact that operating institutions intervene in investors' understanding and availability of information through information misleading and other forms,and then make improper decisions.Secondly,the research on the underlying asset information,risk identification and investor attention driven by big data technology has concluded:First,it combines machine learning and econometric methods to build an explanatory and predictive underlying asset risk identification model,through multiple A comparison of machine learning models shows that Xgboost has advantages in predictability.Through XGboost,the important variables are screened,and the variables that investors should focus on at the level of underlying assets,especially the cost difference between investment and financing;The study found that the information characteristics that characterize the use of big data technology affect the quality of information and then affect the effectiveness of the risk identification model.Whether the platform is connected to the central bank's credit investigation is of great significance for the effective identification of the risk model.The effective investor attention model draws the conclusion that the way investors obtain information has an impact on investor attention.Thirdly,in terms of derivative product information,risk identification and investor attention research under the intelligent investment advisory service.First,according to the investigation of litigation practice,it is concluded that the degree of investor rights transfer has different effects on the suitability of subsequent claims,and then the maturity mismatch risk identification model is constructed;second,by constructing investor attention based on text intelligibility The model,empirically derives the complexity of the contract text and whether there are risk warning clauses,which has an impact on investors identifying the risks of complex financial products assisted by bidding,and provides a reference for proposing a smart investment advisor contract risk disclosure mechanism that eases investors' cognitive bias.Thirdly,in terms of institutional feature information,risk identification and investor attention research using blockchain as a means of risk suppression.One is to construct an institutional risk identification model with explanatory and predictive power,and to screen important variables that have predictive significance for identifying institutional risks through machine learning methods;second,to explore the application of blockchain technology represented by electronic contract deposits.The inhibitory effect of institutional risk,and the conclusion that electronic contract deposits can effectively prevent platform risks;finally,explore the degree of investor attention to the technology that inhibits risks and the other two characteristics of compliance information,and the test shows that investors are in the institution The risk level has a bounded rational conclusion.Finally,study the establishment of an investor committee system under the supervision of the financial supervision and management department and the public security department,from the aspects of three-way due diligence,special audits,etc.,to the construction of protection schemes,the transfer of creditor's rights,and litigation and arbitration.Investor rights protection:Research and establish a new supervision method that replaces rules with principles,replaces ex-post supervision with prior intervention,and replaces rigid norms with flexible management to resolve the fundamental contradiction between technological innovation and legal supervision;research and establishment of institutional transformation process The investor protection mechanism of the company mainly conducts systematic engineering research in the construction of investor information rights system,litigation rights protection mechanism,and investor education system in the financial technology application industry.The value of this article lies in the following:firstly,to cross-integrate financial technology and investor behavior research to build a theoretical framework for risk identification and investor attention from the perspective of financial technology;secondly,to further explore the issue of cognitive bias in investor decision-making.It helps to reveal the cognitive black box of investor behavior and decision-making;the third is to provide evidence support for the improvement of investors' access to information rights system and financial technology supervision sandbox system in the process of technological transformation,and contribute to the modernization of the national governance system and governance capabilities.