A Theoretical Credit Reporting System based on Big Data Concept
| Autor: | Xuan Yang, Wang Jun, Guanzhi Li, Yang Tao |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Government
Computer science business.industry Big data 020206 networking & telecommunications 02 engineering and technology Business model Credit rating Information asymmetry Credit history 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Volatility (finance) business Industrial organization |
| Zdroj: | ICBDE |
| DOI: | 10.1145/3206157.3206163 |
| Popis: | Combining the characteristics of the capital demand scale and cycle volatility caused by the unique seasonal and production organization complexity of the textile and garment industry in Humen- China, the root reasons of difficult financing and high financing costs of the textile and garment enterprises are analyzed, and the fundamental solutions are proposed in this paper. Meanwhile, the guiding and directing role of government in the field of big data application, especially the big data credit collection, is emphasized. The big data technology is well utilized to build big data collection, storage and processing platform based on the big data credit collection. In order to fundamentally solve the problem of financing difficulty in local small and medium-sized enterprise due to long-term data circulation and information asymmetry, a theoretical credit rating model is established and continuously optimized according to the features of textile and garment industry in this area. This report also contributes to the innovation-driven development of local textile and garment enterprises, promotes the management level of enterprises, and improves the innovation ability of business models. |
| Databáze: | OpenAIRE |
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