Data versus Collateral*

被引:33
作者
Gambacorta, Leonardo [1 ,2 ]
Huang, Yiping [3 ]
Li, Zhenhua [4 ]
Qiu, Han [1 ]
Chen, Shu [4 ]
机构
[1] Bank Int Settlements, Basel, Switzerland
[2] CEPR, London, England
[3] Peking Univ, Inst Digital Finance & Natl Sch Dev, Beijing, Peoples R China
[4] Ant Grp, Beijing, Peoples R China
关键词
Big tech; Big data; Collateral; Banks; Asymmetric information; Credit markets; MONETARY-POLICY; DEBT CONTRACTS; HOUSE PRICES; CREDIT; INVESTMENT; CHANNEL;
D O I
10.1093/rof/rfac022
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Using a unique dataset of more than 2 million Chinese firms that received credit from both an important big tech firm (Ant Group) and traditional commercial banks, this paper investigates how different forms of credit correlate with local economic activity, house prices, and firm characteristics. We find that big tech credit does not correlate with local business conditions and house prices when controlling for demand factors, but reacts strongly to changes in firm characteristics, such as transaction volumes and network scores used to calculate firm credit ratings. By contrast, both secured and unsecured bank credit react significantly to local house prices, which incorporate useful information on the environment in which clients operate and on their creditworthiness. This evidence implies that the wider use of big tech credit could reduce the importance of the collateral channel but, at the same time, make lending more reactive to changes in firms' business activity.
引用
收藏
页码:369 / 398
页数:30
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