A Novel Big-Data-Driven Credit Reporting Framework for SMEs in China

Yunchuan Sun, Chunlei Li, Xuegang Cui, Guangzhi Zhang, Xiaoping Zeng, Xueying Chang, Dengbiao Tu, Yongping Xiong
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引用次数: 3

Abstract

SMEs (Small and Medium-size Enterprises) in China always face financing constraints and hardly obtain bank loans under unsound financing system. In external f Academic literature has shown that widespread information asymmetry may prevent the efficient allocation of lending, leading to credit rationing. Currently, most credit reporting, models for SMEs in China are primarily based on hard information about the enterprises and their owners but lack comprehensive evaluation based on the combination with soft information. To bridge the gap for SMEs, we propose a novel big-data-driven credit reporting framework which presents a new credit reporting system by including big data in business, finance, and social networks. The proposed approach features in capturing diversified data online, conducting evaluation and analysis in real-time, and automatically generating online credit reports for SMEs, banks, and government. It also provides an efficient interactive way for SMEs to check credit reports online.
中国中小企业大数据驱动的信用报告框架
中国的中小企业在不健全的融资体系下,一直面临融资约束,难以获得银行贷款。外部学术文献表明,普遍存在的信息不对称可能会阻碍贷款的有效配置,从而导致信贷配给。目前,中国大多数中小企业信用报告模型主要基于企业及其所有者的硬信息,缺乏与软信息相结合的综合评价。为了弥补中小企业的差距,我们提出了一种新的大数据驱动的信用报告框架,该框架通过将商业、金融和社交网络中的大数据纳入其中,提出了一种新的信用报告系统。该方法的特点是在线获取多样化的数据,实时进行评估和分析,并为中小企业、银行和政府自动生成在线信用报告。它还为中小企业提供了一种高效的互动方式,让他们在网上查阅信用报告。
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