| 摘要: |
| 本文首先对互联网金融市场信用风险及其度量方法进行分析；接着结合我国P2P网贷行业的发展情况，分别从上市互联网金融公司和传统金融公司角度对网络借贷平台和银行类上市公司的信用风险的度量模型进行选择；最后将衡量企业违约概率的KMV模型运用到我国上市互联网金融借贷平台和传统金融行业的信用风险度量中，实证分析结果与实际情况以及第三方评估机构所给出的结果具有较高的相符程度，证明KMV模型运用于我国互联网金融借贷平台信用风险度量具有一定的有效性。行业内分析和行业间分析的结果，验证了本文所构建的KMV模型对互联网金融借贷平台信用风险评价模型有着相当高的精度，可以比较准确地度量互联网金融借贷平台的信用风险。 |
| 关键词: P2P网络借贷；信用风险；KMV；互联网金融 |
| DOI： |
| 分类号:F832 |
| 基金项目:安徽省哲学社会科学规划项“互联网金融P2P平台风险预警与管理”（AHSKY2015D53） |
|
| Credit Risk of Internet Finance and Traditional Finance Industry Comparative Research Based on KMV Model |
|
FANG Guo-bin，MA Tian-Chi
|
|
School of Statistics & Applied Mathematics，Anhui University of Finance & Economics
|
| Abstract: |
| Firstly,this paper analyzes the credit risk of the internet financial market and its measurement methods.Then combined with the development of the P2P online lending industry in China，the credit risk measurement models of P2P online lending platforms and listed banks are selected from the perspectives of listed internet finance companies and traditional finance.Finally，the KMV model that measures the probability of corporate default is applied to the credit risk measurement of China’s listed P2P online lending platforms and the traditional financial industry.The empirical analysis results are highly consistent with the actual situation and the results given by third-party evaluation agencies.It proves that the KMV model is applied to the credit risk measurement of China’s P2P listing platform with certain validity.The results of intra-industry analysis and inter-industry analysis verify that the P2P online lending platform credit risk evaluation model constructed in this paper has a fairly high accuracy，and can measure the credit risk of Internet financial lending platforms relatively accurately. |
| Key words: P2P Lending；Credit Risks；KMV；Internet Finance |
