An Empirical Study for Chinese P2P platforms

We discussed few papers focused on US Market, and the main data were Prosper and Lendingclub. We introduce a recent paper regarding Chinese P2P market place. Beginning from the first P2P platform in 2007, the Chinese P2P lending market has developed rapidly. Unlike US market, there is no official credit information related to an individual borrower provided through any agency. As a result, it is difficult for lenders to obtain comprehensive information about borrowers, resulting in a severe hazard of information asymmetry. 

Qizhi Tao, Yizhe Dong and Ziming Lin used data from renrendai (We.com) and explored how borrowers’ financial and personal information, loan characteristics and lending models affect loan funding outcomes. They found that those borrowers earning a higher income or who own a car are more likely to receive a loan, pay lower interest rates, and are less likely to default. The credit grade assigned by the lending platform may not represent the creditworthiness of potential borrowers. They also found that the unique offline process in the Chinese P2P online lending platform exerts significant influence on the lending decision.

The empirical study illustrated the basic fact and implication for Chinese P2P market. However, there are some issues:

1. The credit score are dynamic and update to the latest borrowing. So it could be biased if a borrower require funding more than once. The credit score is A for all pre-approved application from offline source.

2. The paper distinguished the offline and online borrowers, but they didn’t explore how online and offline loans changed over time. The fact is that the offline loans increased rapidly while the online application declined for all successful loans. Offline application charged higher interest rate than the rate appeared on the platform.

3. Based on the data, Offline loans are all successful and no default on any time. Thus, the argument “unique offline process in the Chinese P2P online lending platform exerts significant influence on the lending decision.” could be problematic.

The full paper Click here.

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