Big data pricing in marketplace lending and price discrimination against repeat borrowers: Evidence from China

被引:6
|
作者
Tian, Geran [1 ,2 ]
Wu, Weixing [2 ]
机构
[1] Capital Univ Econ & Business, Sch Finance, Zhangjia Lukou 121, Beijing 100070, Peoples R China
[2] Univ Int Business & Econ, Sch Banking & Finance, Huixindongjie 10, Beijing 100029, Peoples R China
关键词
Big data; Fintech; Marketplace lending; Peer-to-peer lending; Price discrimination; Fair lending; Behavior-based price discrimination; CREDIT MARKETS; ELASTICITIES; DEMAND; GENDER; CONSTRAINTS; BEHAVIOR; RATES;
D O I
10.1016/j.chieco.2023.101944
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this work, we systematically investigate the pricing mechanism change from auction to big data pricing on one of the major marketplace lending platforms in China. We find that big data pricing reduces the average interest rate while the borrowers with delinquency or default his-tories are assigned higher interest rates. However, repeat borrowers are also faced with growing interest rates, even though they have been paying their debts on time. Further analysis shows that repeat borrowers have lower income and education levels. Moreover, investor returns become less dispersed after pricing with big data, which can be a result of homogeneous loans on the market. The implications of the above findings are discussed.
引用
收藏
页数:15
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