Credit bureaus and scoring agencies have played an active part in the impressive growth of consumer credit in the United States at the turn of the twenty-first century. Companies like Equifax (America’s oldest credit bureau) or FICO (providers of the most widely used consumer credit score) have managed to compile a massive volume of consumer histories and translate them into a standardized and objective three-digit number meant to predict the creditworthiness of a person. These companies grew beyond the US borders and expanded to Latin America, where they implemented similar methods. However, they were not as effective in seizing and refining consumer information in a region where almost half of the population lacks access to formal banking networks. This half, furthermore, has been better captured by local or regional financial technology (fintech) firms, that, assisted by artificial intelligence (AI), have managed to successfully lend to and assess borrowers without robust credit histories via the use and sophistication of other sources of information. The goal of this project is to understand the role of credit scoring and other financial technologies in the recent but sustained expansion of credit and indebtedness in the Southern Cone region of Latin America, which includes Argentina, Chile, and Uruguay. This is explored by empirically tracking and comparing the work of Equifax with that of local and regional fintech firms. By tracing the development of financial technologies in South America, this research makes intelligible the role of STEM disciplines in generating new forms of credit and indebtedness in a context where indebtedness rates are on the rise worldwide and credit remains crucial to access education, healthcare, housing, and subsistence. This project contributes to understanding the potential of financial technology to continually reshape socio-economic life.
Drawing on qualitative data collected through in-depth interviews with local experts and industry insiders; participant observation in fintech conferences and seminars; and archival research on company, industry, and public polices, this project responds to two main research questions: a) How are AI and related technologies expanding financial services and reshaping socio-economic life in Latin America? b) What techniques have local fintech firms employed to capture excluded populations, generating knowledge regimes that far surpass what information giants like Equifax can assemble? These questions are explored by looking at the combination of technologies, innovation, and expertise that bring Latin American consumer credit markets into being. Such an approach yields valuable insights on how value and knowledge are produced through technical innovation and on how algorithms generated through machine learning are used to predict economic behaviors, especially in contexts of socio-economic uncertainty. This project builds on a hypothesis that states that the shallow reach of formal financial infrastructures in South America placed limits on Equifax’s capacity to expand, whereas regional fintech firms were able to take advantage of this infrastructural deficit by developing techniques for assessing creditworthiness by translating novel forms of data into commercially useful knowledge.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
