Abstract:
Based on 388522 loans of Renrendai.com, this paper makes the special dictionary in P2P lending and analyzes how the signaling of words in descriptions affect the behaviors in network lending. The empirical results show the following conclusions. First, the signals of the different kinds of words in descriptive texts provided by P2P borrowers have significant impacts on lenders' decision-making. The proportion of positive words and the proportion of financial words are positively related with the success rate. The proportion of negative words, the proportion of strong modals and the proportion of weak modals are negatively related with the success rate. Second, when the borrowers are of different age levels and income levels, the word signals of their descriptive texts have significantly different influences on lenders' decision-making. And the difference of gender and the different levels of education almost have no effect on the word signals. Finally, the quality signals of different kinds of words are partly effective in the lenders' decision-making. To be specific, the signals of financial words are effective and they are identified correctly by investors. The signals of strong modals are also effective but they are not recognized correctly by lenders. Other categories of words are not effective signals.
彭红枫, 林川. 言之有物:网络借贷中语言有用吗?——来自人人贷借款描述的经验证据[J]. 金融研究, 2018, 461(11): 133-153.
PENG Hongfeng, LIN Chuan. Arguments in Substances: Are Words Useful in P2P Lending?: Evidence from Descriptions of Loans in Renrendai.com. Journal of Financial Research, 2018, 461(11): 133-153.
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