Paper short abstract:

The paper analyses the commodification of personal data and debt in Brazil and the role of opaque credit criteria. It discusses the implications for automating inequality in Brazil’s credit society and methodological challenges in researching an opaque industry.

Paper long abstract:

In the era of Brazil’s “fintech revolution”, data driven technologies including algorithmic assessments of credit-worthiness have facilitated the expansion of credit to the low-income population (Miller 2003, vii, Fourcade and Healey 2013). As people have come to heavily rely on credit for daily living and life projects in the aftermath of the Covid-19 pandemic and economic crisis, access and assessments have become pivotal in people’s lives. Meanwhile, as observed by Fourcade and Healy: “The basis upon which people are being scored, rated and evaluated is less predictable, or even knowable, to most of those who rely on it” (2017: 11). As this paper will show, this is also the case for many of the employees offering credit. Based on multimodal fieldwork, the paper seeks to unpack “the black box” of Brazil’s credit industry in which people’s private data and debt is being commodified by financial actors to generate profit. It will discuss the methodological paradox of doing fieldwork among consumers and servicers for whom credit is vital to their lives and businesses and yet the conditions on which it is offered is opaque. While opacity is in fact intrinsic to the business model, consumers’ lack of knowledge is cast as “financial illiteracy”. By engaging with critical studies of financial extractivism (Bernards 2022; Gago and Mezzadra's 2017) and datafied capitalism (Burrell and Fourcade 2021), the paper examines the capitalist experimentation and expansion of “subprime empire” (Schuster and Kar 2021) as it plays out in Brazil and its implications for automating inequality.