Innovative Research Of Online And Offline Loans For Incubator Enterprise Cluster Based On Internet Banking

Business incubator is an agency that nurtures high-tech enterprise and provides infrastructuresupport and service support for small and medium micro enterprises which can effectively reducethe risk and cost. Incubator nurtures incubated enterprises effectively promote the development ofhigh-tech industries. However, for incubator companies, a shortage of funds is the most prominentissues. The most common replenishment is bank loans for business incubators. However, due tothe external security system is imperfect and small micro-enterprise incubator’s bad financial data,small micro-enterprise can not be provided mortgage loans by banks, resulting in an incubatorbusiness loans difficulty. Therefore, the article chooses incubator enterprise clusters for the study,hoping to open up new financing channels, abundant financing products to solve businessincubator financing difficulties.The research ideas of this paper includes following four points. In the study, focusing on theproblem of financing the enterprise incubator and its innovative loan products. In research ideas,this paper analyzes the overall business process cluster loans, including loans of membersoptimization, pricing cluster loans and other business risk business risk regulatory supervision. Onproduct model, I research cluster loans online, offline and online and offline phasor combinationof model and provide more financing channels to enterprise incubator.The first chapter, by focusing on the major cities of the incubator companies conduct researchand interviews clusters, I understand and analyze the current situation of the incubator corporatefinance. The second chapter, I study on the current financial status of the Internet, the Internetfinancial model,the financial impact of the Internet on credit, and loan innovative products andpricing models. This paper focuses on the default intensity models and Copula theory and lays thefoundation for subsequent content. The third chapter, based on industry-wide promotion of thecluster loan financing pattern, this paper put forward innovative business incubator cluster loans’sonline, lines and phasor combination of online and offline pattern. Hoping networking platformcan be built to meet the requirements of the cluster group loan companies. The forth chapter, Ifirstly optimize the member of the cluster, and then introduce the model of cluster lending linepricing. Using the multivariate Gaussian Copula and Intensity model price the loan. For onlinepricing section, I analysis the similarities and differences between online and offline cluster loans.And then use the information processing Logistic model to calculate default rates and use of theBenefit maximization model to solve a transaction set. The fifth chapter, make policyrecommendations to the regulatory and institutional innovation cluster loans.Ultimately, the cluster loans online and offline pattern can provide a richer source of fundingto incubated enterprises. Guarantees between enterprise cluster group members increase creditand guarantees are jointly and severally liable with each other. Clusters loans increase the successrate of the loan, reducing the risk of loans. In the pricing model, through numerical analysis thestudy confirmed the feasibility of the model, and has certain guiding significance for the clusterloan pricing.