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THE NORMS OF ALGORITHMIC CREDIT SCORING

Published online by Cambridge University Press:  30 March 2021

Nikita Aggarwal
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Abstract

This article examines the growth of algorithmic credit scoring and its implications for the regulation of consumer credit markets in the UK. It constructs a frame of analysis for the regulation of algorithmic credit scoring, bound by the core norms underpinning UK consumer credit and data protection regulation: allocative efficiency, distributional fairness and consumer privacy (as autonomy). Examining the normative trade-offs that arise within this frame, the article argues that existing data protection and consumer credit frameworks do not achieve an appropriate normative balance in the regulation of algorithmic credit scoring. In particular, the growing reliance on consumers’ personal data by lenders due to algorithmic credit scoring, coupled with the ineffectiveness of existing data protection remedies has created a data protection gap in consumer credit markets that presents a significant threat to consumer privacy and autonomy. The article makes recommendations for filling this gap through institutional and substantive regulatory reforms.

Keywords

algorithmic credit scoringconsumer financeartificial intelligencemachine learningdata protectionprivacyGDPR
Type
Articles
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The Cambridge Law Journal , Volume 80 , Issue 1 , March 2021 , pp. 42 - 73
Copyright
Copyright © Cambridge Law Journal and Contributors 2021

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Footnotes

*

DPhil candidate, University of Oxford.

I would like to thank the following for their very helpful comments on earlier versions of this article: John Armour, Dan Awrey, Ryan Calo, Ignacio Cofone, Hugh Collins, Horst Eidenmüller, Mitu Gulati, Geneviève Helleringer, Ian Kerr, Bettina Lange, Tom Melham, Jeremias Prassl, Srini Sundaram, David Watson, participants in the Virtual Workshop on ML and Consumer Credit and workshops at the University of Montreal, McGill University, Singapore Management University, University of Luxembourg, Sciences Po, European University Institute, and University of Oxford (Faculty of Law and Oxford Internet Institute).

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