 Data versus Collateral*Leonardo Gambacorta, Yiping Huang, Zhenhua Li, Han Qiu and Shu Chen Review of Finance, 2023, vol. 27, issue 2, 369-398 Abstract: 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. Keywords: Big tech; Big data; Collateral; Banks; Asymmetric information; Credit markets (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:oup:revfin:v:27:y:2023:i:2:p:369-398. Ordering information: This journal article can be ordered from Access Statistics for this article Review of Finance is currently edited by Marcin Kacperczyk More articles in Review of Finance from European Finance Association Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC. |
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