大数据征信的信贷效用——基于中小微企业的理论与实证分析  

The Credit Utility of Big Data Credit:Based on Theoretical and Empirical Analysis of SMEs’ Capacity

作　　者：胡倩倩 池仁勇[2] Hu Qianqian;Chi Renyong(Business School,Zhejiang University of Technology,Hangzhou 310000;China Institute of Small and Medium Enterprises,Zhejiang University of Technology,Hangzhou 310000)

机构地区：[1]浙江工业大学管理学院,杭州310000 [2]浙江工业大学中国中小企业研究院,杭州310000

出　　处：《管理评论》2022年第12期86-96,108,共12页Management Review

基　　金：国家社会科学基金重大项目(17ZDA088);浙江省社会科学规划基金重大项目(18ZDWT03ZD);浙江省大学生科技创新活动计划(新苗人才计划)(2018R403082)

摘　　要：中小微企业信贷融资难问题依然突出,信息不对称的根本原因突显。而大数据征信作为问题解决的关键所在,其整体建设有待加强。本研究以2013—2017年30个省级行政区为样本,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。研究表明,大数据征信建设能有效提升中小微企业信贷能力,且该效用随着时间推移有增强趋势,受企业软硬信息、区域金融发展水平等交互影响。研究认为强化大数据征信顶层设计,健全制度保障体系,拓展大数据征信应用场景,推进金融体系创新改革,进而充分发挥大数据征信效用,是全面提升中小微企业信贷能力的关键路径。The availability credit financing remains limited for SMEs and the root cause lies in information asymmetry.big data credit is a key to solving this problem,but its construction needs to be strengthened.For this purpose,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 analyze the relationship between the construction of big data credit and SMEs’credit ability from both macro and micro perspectives.The study shows that,big data credit construction can indeed improve SMEs’credit capacity,and this effect has an increasing trend with the passage of time.At the same time,the effect is affected by the interaction of soft and hard information of enterprises and the level of regional financial development.Therefore,it is advised to strengthen the top-level design of big data credit,improve institutional guarantee system,expand the application scenario of big data credit,promote financial system innovation and reform,and give full play to the synergy effect of big data credit in order to comprehensively improve the credit ability of small and medium-sized enterprises.

关 键 词：大数据征信 中小微企业 信贷效用 分层线性模型 

分 类 号：F832.4[经济管理—金融学] F276.3