Playing the credit score game: algorithms, 'positive' data and the personification of financial objects
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 tha...
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| Published in | Economy and society Vol. 46; no. 3-4; pp. 346 - 368 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Abingdon
Routledge
02.10.2017
Taylor & Francis LLC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0308-5147 1469-5766 |
| DOI | 10.1080/03085147.2017.1412642 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Kear, Mark |
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| SubjectTerms | algorithmic governance Algorithms Arbitration Bias Case studies Computation Consumer credit Credit Credit reports credit score Credit scoring datafication Financial inclusion Marginality Markets Scores subject formation Technology |
| Title | Playing the credit score game: algorithms, 'positive' data and the personification of financial objects |
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