Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IIKI.2016.46 | 2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI) |
Keywords | Field | DocType |
SME financing constraints,Information asymmetry,Credit reporting,Comprehensive evaluation,Big data | Credit history,Information asymmetry,Social network,Soft information,Computer security,Computer science,China,Credit rationing,Finance,Big data,Government | Conference |
ISBN | Citations | PageRank |
978-1-5090-5953-9 | 0 | 0.34 |
References | Authors | |
1 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunchuan Sun | 1 | 534 | 54.06 |
| Chunlei Li | 2 | 0 | 0.34 |
| Xuegang Cui | 3 | 0 | 0.34 |
| Guangzhi Zhang | 4 | 9 | 3.20 |
| Xiaoping Zeng | 5 | 236 | 29.69 |
| Xueying Chang | 6 | 0 | 0.34 |
| Dengbiao Tu | 7 | 0 | 0.34 |
| Yongping Xiong | 8 | 362 | 18.61 |