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Alipay's 'Ant Credit Pay' meets China's factory workers: the depersonalisation and re-personalisation of online lending.
- Source :
- Journal of Cultural Economy; Feb2021, Vol. 14 Issue 1, p87-100, 14p
- Publication Year :
- 2021
-
Abstract
- Scholarly accounts of the global rise of statistical credit scoring technologies have tended to portray these automated, digitised systems as supplanting human involvement in lending. This paper examines Chinese migrant factory workers' encounters with Ant Credit Pay, Alipay's novel consumer credit facility (which utilises the Zhima Credit scoring system). Drawing on ethnographic data, we document how workers come to understand Ant Credit Pay through the depersonalising and re-personalising processes they associate with it. Workers prefer its depersonalised mode of lending over borrowing from banks, friends, or family. However, they nonetheless also attempt to re-personalise Ant Credit Pay through propagating the belief that human-style logics underlie its scoring mechanisms. This becomes evidenced through workers' integration of the platform into their personal spending practices, alongside their portrayal of charismatic Alipay founder Jack Ma as the orchestrator of the platform's novel approach to lending. We argue that acknowledging Ant Credit Pay's consolidation of depersonalising and re-personalising qualities necessitates the productive analysis of digital credit as a human-machine assemblage. Furthermore, this financial object – and workers' engagement with it – is generative of a distinctive personhood that concretizes China's ongoing social transformation, while also carrying implications for understanding current global trends towards the digitisation of credit. [ABSTRACT FROM AUTHOR]
- Subjects :
- CREDIT scoring systems
INDUSTRIAL workers
CONSUMER credit
CREDIT ratings
CREDIT
Subjects
Details
- Language :
- English
- ISSN :
- 17530350
- Volume :
- 14
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Journal of Cultural Economy
- Publication Type :
- Academic Journal
- Accession number :
- 147988392
- Full Text :
- https://doi.org/10.1080/17530350.2020.1763424