当今大数据概念深入人心,网络金融借贷在此背景下蓬勃发展,而其行业风险也在不断上升,出现了网络借贷平台存活时间短,行业较为复杂混乱的乱象.由此,我们项目以大数据为背景,结合网络金融借贷行业发展现状和国内外典型平台案例分析,测算风险因素,通过建立风险预警模型,进行定性和定量分析,并实际应用于我国现有借贷行业与平台,找出缺漏不断完善.从而为金融借贷行业降低风险,建立借贷安全保障,提供一种风险预警模型和定性分析的参考方法,并帮助个人与企业进行借贷决策给出意见,减少风险因素;以响应我国十八大提出的"打造互联网金融服务平台"的号召.%At present, because of spreading of the concept of Big Data, the P2P leading developed a lot, while, we couldn't ignore the ascending of the risks. There came a phenomenon that some P2P platforms could not stay long, and this industry was a bit disordered. So, our project based on the big data, combining about the present developing situation of P2P industry and the cases from domestic and overseas. Then, we calculated the risk factors, and made the risk warning model, then, did the qualitative and quantitative analysis, so that this model could be practical used into the P2P platforms of our country to find the loopholes. It aimed to pull the risks of financial credit down and build the security assurance. The most important one is to provide a risk warning model and the reference method for analyzing, also giving some suggestions for individuals or enterprises' decision maker to consider credit to cut down the risks, which responded the government's policies.
展开▼
