Playing the credit score game

Algorithms, ‘positive’ data and the personification of financial objects

Bibliographic Data

ID24304513
AuthorsMark Kear (0000-0003-3998-3481, School of Geography & Development, University of Arizona, ENR2, room S515, 1064 E Lowell Street, PO Box 210137, Tucson, Arizona, 85721, USA.)
Year2017
Volume46
Issue3-4
Pages346-368
Publication date2017-10-02
Open AccessNo
TypeARTICLE
VenueEconomy and Society (JOURNAL)
Journal identifiersISSN: 0308-5147 • E-ISSN: 1469-5766
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/03085147.2017.1412642
OpenAlexW2783343898
LanguageEN
Citations received29
References cited42

This paper is about how people are learning to ‘make themselves up’ in response to the market’s new algorithmic ways of seeing. More specifically, it explores how the self-datafication of informal financial relations is being used to affect the calculation of credit score. I argue that credit score functions as a legal technology of arbitration beset with contradictions that are giving rise to inchoate struggles over the distribution of calculative agency in consumer credit markets. Drawing on an ethnographic case study of credit building peer ‘lending circles’, the paper explores how financially marginalized groups and financial inclusion advocates are reacting to the blind spots and biases of credit-scoring algorithms through compensatory and transgressive data-generation practices.

algorithmic bias · algorithmic credit scoring · credit building · credit scores · data practices · Financial inclusion · peer-to-peer lending · Ethics and Social Impacts of AI · FinTech, Crowdfunding, Digital Finance · Microfinance and Financial Inclusion