基于互联网金融的孵化器企业集群线上线下贷款创新研究

发布时间：2018-01-12 07:31

本文关键词：基于互联网金融的孵化器企业集群线上线下贷款创新研究　出处：《华南理工大学》2014年硕士论文　论文类型：学位论文

【摘要】：企业孵化器是作为培育和扶植高新技术企业的机构，能有效地降低企业的风险和成本，提高企业的创业成功率。在孵化器企业的培育过程中，资金短缺是中小微企业面临的最突出问题。寻求银行贷款是孵化器企业最常用的融资模式。但，由于外部担保体系的不完整、孵化器中小微企业自身经济实力的不足等，与传统银行的“抵押担保”措施不相符，导致孵化器企业贷款难。因此，本文以孵化器企业集群为研究对象，希望能开辟新的融资渠道、丰富融资产品，解决孵化器企业融资难。本文的研究思想：在研究对象上，着眼于在孵企业的融资难问题，对其贷款产品进行创新；研究思路上，从整体业务流程上对集群贷款进行分析，涉及贷款成员的优化问题、集群贷款的定价问题，以及贷款业务风险监管等；产品模式上，研究集群贷款线上、线下及线上线下相结合的模式，，为孵化器企业的融资提供了更多的融资渠道；模型方法上，线下定价将贷款模型推广至多元，线上定价首先运用Logistic模型进行信息处理，再用效用最大化模型求解利率。线上与线下相结合定价采用线性规划对贷款组合进行优化。本文的研究方法与内容：通过对全国各大重点城市的孵化器企业集群进行调研和访谈，了解和分析了孵化器企业融资现状。并对目前互联网金融的现状、互联网金融模式进行研究，综述了互联网金融对信贷的影响、目前已有的贷款创新产品及其定价模型。针对孵化器企业融资难问题，本文基于业界推广度较广的集群贷款融资模式,创新性的提出孵化器企业集群贷款的线上、线下以及线上线下相结合的模式，通过鼓励银行等机构建立网络金融平台，对符合条件的集群小组企业进行贷款发放。而后，围绕集群贷款的线上、线下定价流程，先对集群贷款成员进行优化分析，然后介绍了集群贷款线下定价的模型，用多元高斯Copula和强度模型实现定价。在线上定价部分，先分析了线上与线下集群贷款的异同，而后用Logistic模型进行信息处理计算违约率，利用效益最大化模型求解可能性交易集合，最终得出线上贷款利率。文章的最后，对集群贷款监管与制度创新提出政策建议。本文研究的线上线下集群贷款模式能够为在孵企业提供更丰富的融资途径，有别于传统的抵押担保贷款，通过企业集群小组成员之间的互相担保增信、承担连带责任，提高了贷款成功率，降低贷款风险。而在定价模型中，本文通过数值分析正式了模型具有可行性，对集群贷款定价具有一定的指导意义。
[Abstract]:Business incubator is an institution to cultivate and foster high-tech enterprises, which can effectively reduce the risks and costs of enterprises, improve the success rate of enterprises. In the incubation process of incubator enterprises. Capital shortage is the most prominent problem faced by small and medium-sized enterprises. Seeking bank loans is the most commonly used financing mode for incubator enterprises. However, due to the incomplete external guarantee system. The shortage of economic strength of small and micro enterprises in incubator does not accord with the "mortgage guarantee" measures of traditional banks, which leads to the difficulty of lending to incubator enterprises. Therefore, this paper takes the cluster of incubator enterprises as the research object. Hope to open up new financing channels, enrich financing products, and solve the financing difficulties of incubator enterprises. The research idea of this paper: on the research object, focusing on the financing difficulty of incubated enterprises, innovating its loan products; Research ideas, from the overall business process of the analysis of cluster loans, involving the optimization of loan members, the pricing of cluster loans, as well as loan business risk supervision and so on; On the product model, the research on the combination of cluster loan line, offline and online provides more financing channels for incubator enterprises. In the model method, offline pricing extends the loan model to the maximum element, and the online pricing first uses Logistic model to process the information. Then the utility maximization model is used to solve the interest rate, and the linear programming is used to optimize the loan portfolio by the combination of online and offline pricing. The research methods and contents of this paper: through the investigation and interview of the incubator enterprise cluster in the major cities of the country, understand and analyze the current situation of the incubator enterprise financing, and the current situation of the Internet finance. This paper studies the Internet finance model, summarizes the impact of Internet finance on credit, the existing loan innovation products and their pricing models, and aims at the financing difficulties of incubator enterprises. Based on the cluster loan financing model which is widely popularized in the industry, this paper innovatively puts forward the online, offline and offline combination model of incubator enterprise cluster loan. By encouraging banks and other institutions to establish a network financial platform to provide loans to eligible cluster group enterprises. Then, around the online and offline pricing process of cluster loans. This paper first analyzes the members of the cluster loan, then introduces the pricing model under the cluster loan line, and uses the multiple Gao Si Copula and intensity model to realize the pricing. Firstly, the similarities and differences between online and offline cluster loans are analyzed, and then the default rate is calculated by using Logistic model to calculate the default rate, and the possibility transaction set is solved by using the benefit maximization model. At the end of the article, some suggestions on the supervision and institutional innovation of cluster loan are put forward. The online and offline cluster loan model studied in this paper can provide more abundant financing channels for incubated enterprises, different from the traditional mortgage guarantee loan, through mutual guarantee and credit enhancement among the members of the enterprise cluster group. Taking joint and several liability improves the loan success rate and reduces the loan risk. In the pricing model, the model is feasible through numerical analysis, which has certain guiding significance for the pricing of cluster loans.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F276.44;F832.4

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