Xu, Ruowen (2020) Big data credit scoring in China : organisation of work, state aspiration and impact on financial inclusion. PhD thesis, University of Warwick.

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Abstract

This thesis examines the configuration of Big Data algorithmic credit scoring. It is situated within the context of the Chinese government’s programme to construct a social credit system. Based on ethnographic fieldwork in a credit modelling team of a major internet company in China, the findings of this thesis provide organisational-level evidence regarding the various critical factors influencing the design, modelling, usability and outcome of the configuration of credit models. The three empirical chapters respectively reveal the organisation of data science work , organisational innovation of technology in delivering on state aspirations and the societal consequences of the Big Data driven quantification of creditworthiness. The thesis contributes to the literature on technological affordance, governmentality literature on calculative technology, and to literature on calculative cultures by offering a rich empirical analysis of algorithmic credit scoring in China. The findings are of interest to scholars researching the future of work, the production of algorithmic measures and the socio-economic impacts of calculative devices. The findings should also be of practical interest to organisations building data science teams, to policy makers designing state calculaive programmes and to parties concerned about the impact of algorithmic decision making on financial inclusion.

Item Type:	Thesis or Dissertation (PhD)
Subjects:	H Social Sciences > HG Finance
Library of Congress Subject Headings (LCSH):	Credit scoring systems -- China, Credit control -- China, Big data -- China, Big data -- Government policy -- China, Automatic data collection systems, Social credit -- China
Official Date:	December 2020
Dates:	Date Event December 2020 UNSPECIFIED
Institution:	University of Warwick
Theses Department:	Warwick Business School
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Millo, Yuval, 1969- ; Spence, Crawford
Format of File:	pdf
Extent:	198 leaves : illustrations (some colour)
Language:	eng

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