Empirical Research On Investing Behaviors On P2P Online Lending Platforms

Since 2007 when ppdai.com introduced P2P online lending to China, P2P online lending has achieved impressing growth. However, it also brought about some problem like high default rate, which made it very controversial. Currently there are only a few studies about P2P online lending platforms. Most of them are descriptive review introducing the experience of online lending platforms abroad, or trying to propose some advice on regulations over P2P online lending. Based on the existing empirical researches, the focus of study on P2P online lending in China is about the influence of borrower’s credit rating on the probability of success. There is neither research on how investors utilize soft information like borrower description, borrower picture, and borrower finance description, nor research on the herding behaviors among investors. Thus, our research tries to fill the blank of domestic studies.We find out that investors on ppdai.com are not sensitive to the soft information of borrowers. It doesn’t matter for investors whether or not borrowers describe themselves in detail, or fully explain why the want to borrow. Investors are not interested in borrower’s pictures, neither. Investors may ignore soft information because the amount is tiny for them while the analysis of software is too complicated. And it’s the first research result about soft information utilization on P2P lending platform in China. Like other researches, we also find that borrower credit rating is most influential for the probability of success.Interestingly, investors also ignore the default history of borrowers when they make decisions. It’s quite opposite to our common sense. The reasons may be that people can’t find the information due to poor website design.We also confirm that there is severe herding behavior on ppdai.com. Most of the listings get no bids at all, but once they get one bid, they scarcely lose the game. Among all 3000 samples, there are only 2 samples, which got bids but still fail at last. We found the higher the participation rate, the more money the listing received every minute.