标题:Big-data-driven Model Construction and Empirical Analysis of SMEs Credit Assessment in China
作者:Liu Yadi; Song Yuning; Yu Jiayue; Xie Yingfa; Wang Yiyuan; Zeng Xiaoping
通讯作者:Zeng, XP
作者机构:[Liu Yadi] North China Univ Water Resources & Elect Power, Zhengzhou, Henan, Peoples R China.; [Song Yuning] Shandong Univ, Jinan, Shandong, Peoples 更多
会议名称:7th International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)
会议日期:OCT 19-21, 2018
来源:2018 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS
出版年:2019
卷:147
页码:613-619
DOI:10.1016/j.procs.2019.01.205
关键词:Small and Medium-size Enterprises; Financing constraints; Credit; Assessment; Big data
摘要:Most of SMEs(Small and Medium-size Enterprises) in China are facing severe fmancing constraints, while credit reporting could be effective to help overcome it. However, traditional credit reporting mainly based on fmancial data, can hardly give a wellrounded evaluation on SMEs limited on financial data while flourished in non-financial data. In this work, we propose a big-data driven credit assessment framework for SMEs, highlighting the combination of financial and non-financial data including big data from business, government, social media & networks. An application to 123 SMEs in China inllustates that our methodology outperforms the traditional one, especially for those SMEs of worse financial conditions. (C) 2019 The Authors. Published by Elsevier B.V.
收录类别:CPCI-S
资源类型:会议论文
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