中小微企业作为国民经济发展的重要推动力，其融资困境却仍旧没有得到有 效改善。在该种情况下，社会各界越来越关注中小微企业信贷融资难问题的根本 原因——信贷双方信息不对称，并尝试通过大数据征信建设，提升信贷市场信息 透明度以及共享水平，降低借款方道德风险、逆向选择等发生概率，最终帮助中 小微企业提升整体信贷能力。但反观现今大数据征信建设，其发展仍旧处于初步 阶段，行业监管、法律完善、中小微企业有效对接等方面均还存在许多不足之处。 同时，在学术研究上，我国征信研究起步较晚，大多以理论论述、政策分析或国 外案例研究为主，定量实证研究偏少，计量方法精准度和拒真概率也还有待提高。 因此，本文以2013-2017年中小企业板和创业板企业为研究样本，从宏微观 双视角出发，结合区域金融发展水平的外在调节作用以及企业软硬信息的内在影 响，运用分层线性模型定量分析了大数据征信建设与中小微企业信贷能力之间的 影响关系，以期丰富现有研究视角，并为大数据征信建设提供理论依据和决策参 考，进而帮助中小微企业信贷能力提升。 研究发现，（1）大数据征信建设确实能够提升中小微企业信贷能力，且该积 极作用随着时间推移有增强趋势。（2）企业规模、运营年限、内部控制能力等软 硬信息均会对中小微企业信贷能力产生影响，且大数据征信建设在该影响过程中 起到部分调节作用，即大数据征信建设能减弱运营年限负向效用以及内部控制能 力正向效用。（3）大数据征信建设与区域金融发展水平相辅相成，协同推动中小 微企业信贷能力提升；其中，大数据征信建设与信贷资金分配效率交互效应为正， 与金融业竞争水平交互效应为倒U型。 关键词：大数据征信，中小微企业，信贷能力，分层线性模型 大数据征信建设与中小微企业信贷能力的关系研究 II RESEARCH ON THE RELATIONSHIP BETWEEN THE CONSTRUCTION OF BIG DATA CREDIT AND THE SMES CREDIT ABILITY ABSTRACT As an important driving force for the development of the national economy, small and medium-sized enterprises have not effectively ameliorate the financing dilemma. Under the above circumstance, all sectors of society are paying more and more attention to the root cause of the SMEs credit difficulty-- asymmetric information between credit parties, and try to improve the information transparency and sharing of credit market information through the big data credit construction, which can finally help SMEs improve their overall credit capacity. However, the construction of big data credit is still in its infancy. There are still many shortcomings in the aspects of industry supervision, legal improvement, effective docking of small and medium-sized enterprises, and so on. At the same time, in the field of academic research, Chinese credit research started late, and mostly based on theoretical discourse, policy analysis or foreign case studies. Besides the quantitative empirical research is less, and the accuracy of measurement methods and the probability of rejection still need to be improved. Therefore, this paper takes the SME board and the carve out board in 2013-2017 as the research samples, and uses the hierarchical linear model to analysis the relationship between the construction of Big Data credit and the SMEs credit ability from the perspective of macro and micro. Throughout the research process, this paper also combines the external regulation of regional financial development level and the 浙江工业大学硕士学位论文 III intrinsic influence of enterprise soft and hard information. In general, this study aims to enrich the existing research perspective and provide theoretical basis and decision- making reference for the construction of big data credit, which will help improve SMEs credit capacity. The study shows that, (1) big data credit construction can indeed improve the SMEs credit capacity, and this positive effect has an increasing trend with the passage of time. (2) Soft and hard information such as enterprise size, business age and internal control capability will have an impact on the SMEs credit capacity, and the construction of big data credit will play a part in regulating the impact. That is, the construction of big data credit information can reduce the negative effect of business age and the positive effect of internal control capabilities. (3) The construction of big data credit and the level of regional financial development complement each other, and jointly promote the SMEs credit capacity. Among them, the interaction effect between big data credit construction and credit fund allocation efficiency is positive, and the interaction effect with the financial industry competition level is inverted U-shaped. KEY WORDS: big data credit, small and medium-sized enterprises, credit capacity, hierarchical linear model 大数据征信建设与中小微企业信贷能力的关系研究 IV 目 录 摘要 .............................................................................................................................I ABSTRACT .................................................................................................................. II 1 绪论 ......................................................................................................................... 1 1.1 研究背景及意义 .......................................................................................... 1 1.1.1 研究背景 ............................................................................................ 1 1.1.2 研究意义 ............................................................................................ 3 1.2 研究思路与方法 .......................................................................................... 3 1.2.1 研究思路 ............................................................................................ 3 1.2.2 研究方法 ............................................................................................ 4 1.3 研究创新点 .................................................................................................. 4 1.4 论文结构安排 .............................................................................................. 5 2 理论基础与文献综述 ............................................................................................. 7 2.1 大数据征信 .................................................................................................. 7 2.1.1 大数据征信相关概念 ........................................................................ 7 2.1.2 大数据征信发展相关研究 ................................................................ 8 2.1.3 大数据征信建设度量 ...................................................................... 12 2.2 中小微企业信贷能力 ................................................................................ 13 2.2.1 中小微企业信贷能力相关概念 ...................................................... 13 2.2.2 企业信贷融资难成因研究 .............................................................. 15 2.2.3 企业信贷能力影响因素研究 .......................................................... 16 2.2.4 企业信贷能力度量 .......................................................................... 19 2.3 大数据征信对中小微企业信贷的作用机制研究 .................................... 20 2.3.1 信息不对称基础理论层面 .............................................................. 20 2.3.2 大数据征信作用流程层面 .............................................................. 21 2.3.3 大数据征信作用对象层面 .............................................................. 21 2.3.4 大数据征信与其他因素综合作用层面 .......................................... 23 2.4 文献述评 .................................................................................................... 23 3 我国大数据征信的实践 ....................................................................................... 24 3.1 征信发展模式方面 .................................................................................... 24 3.2 征信平台建设方面 .................................................................................... 24 浙江工业大学硕士学位论文 V 3.3 信制度与监管体系建设方面 .................................................................... 26 3.4 中小微企业服务方面 ................................................................................ 29 3.5 大数据征信发展难题 ........................................