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Research on P2P Network Loan Risk Evaluation Based on Generalized DEA Model and R-Type Clustering Analysis under the Background of Big Data

机译:基于广义DEA模型的P2P网络贷款风险评估研究和大数据背景下的R型聚类分析

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Internet financial risk is not only directly related to the operation and development of the Internet financial system itself, but also has a very important impact on the country’s macroeconomic operation because of its rapid development speed and growing scale of development. As of February 2017, there were 2335 network loan platforms, among which 55 platforms for problem existed. The event, similar to the platform responsible person absconded with money frequently occurred due to lax supervision, credit risk and so on. Therefore, it is very important to evaluate the financial risks of Internet scientifically. This paper takes the top 100 P2P network loan platform risk controls, obtained the net loan home’s rating authentication, as the main research object. The evaluation index system is structured from three dimensions, respectively as follows: liquidity risk, market risk and credit risk. The R-type cluster analysis is used to reduce the dimension of the index system, and the core index evaluation system is obtained finally. On the basis of this, the risk control capability efficiency of that was evaluated for the first time by the classical DEA-CCR model, and then carried out the excellent, the good, the medium and the poor risk control capacity efficiency rating according to the pre-set step size. The excellent refers to the network loan platforms whose ranking is in the first quarter of the comprehensive efficiency derived by DEA-CCR; non-excellent network loan platform refers to the study of 100 network lending platforms in addition to the excellent lending platform other than the research platform. Taking the Excellent P2P network loan platforms as the reference set and the Non-excellent as the evaluation set, this paper also uses the new generalized DEA model to carry on the research of the “catch-up efficiency” and projection analysis, and obtains the projection value of the non-excellent network lending platform, that is, the improvement value of the non-excellent network lending platform in each research index, and provides a feasible way for the non-excellent P2P network loan platforms to change to the excellent P2P network loan platforms.
机译:互联网财务风险不仅与互联网金融系统本身的运作和开发直接相关,而且由于其快速发展速度和发展规模的发展,对该国的宏观经济运行也具有非常重要的影响。截至2017年2月,有2335个网络贷款平台,其中存在55个问题平台。事件,类似于持有的平台负责人潜逃,经常发生由于LAX监督,信用风险等。因此,科学评估互联网的财务风险非常重要。本文取得了前100名P2P网络贷款平台风险控制,获得了净贷款家庭的评级认证,作为主要研究对象。评估指标系统分别从三维构成,如下:流动性风险,市场风险和信用风险。 R型集群分析用于减少索引系统的尺寸,最后获得核心指标评估系统。在此基础上,通过经典的DEA-CCR模型首次评估该风险控制能力效率,然后进行了优异的,良好,培养基和差的风险控制能力效率等级预设步长。卓越的是指网络贷款平台,其排名是DEA-CCR衍生的综合效率的第一季度;非优质网络贷款平台是指除了研究平台以外的优秀贷款平台之外还为100个网络借贷平台的研究。以优秀的P2P网络贷款平台为参考集和非优异的评估集,本文还采用了新的广义DEA模型进行了“追赶效率”和投影分析的研究,并获得了非优秀网络借贷平台的投影值,即每个研究指标中非优秀网络贷款平台的改进值,为非优质的P2P网络贷款平台提供了一种可行的方式,以改变为优秀的P2P网络贷款平台。

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