{"title":"中国中小企业大数据驱动的信用报告框架","authors":"Yunchuan Sun, Chunlei Li, Xuegang Cui, Guangzhi Zhang, Xiaoping Zeng, Xueying Chang, Dengbiao Tu, Yongping Xiong","doi":"10.1109/IIKI.2016.46","DOIUrl":null,"url":null,"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.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Novel Big-Data-Driven Credit Reporting Framework for SMEs in China\",\"authors\":\"Yunchuan Sun, Chunlei Li, Xuegang Cui, Guangzhi Zhang, Xiaoping Zeng, Xueying Chang, Dengbiao Tu, Yongping Xiong\",\"doi\":\"10.1109/IIKI.2016.46\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":371106,\"journal\":{\"name\":\"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IIKI.2016.46\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIKI.2016.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Big-Data-Driven Credit Reporting Framework for SMEs in China
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.