Algorithms and Discrimination: The Case of Credit Scoring in Brazil

The presentation aims at analyzing how the current debate on algorithmic discrimination is reflected in the case of credit scoring in Brazil. Firstly, I dis¬cuss the concepts of algorithm and algorithmic discrimination and explains why such concepts are particularly meaningful in a data-driven economy. It presents how Big Data, combined with algorithms, has fundamentally altered some decision-making process in our everyday lives, and turns to one application in particular – credit scoring – to discuss how this may pose challenges for Brazilian law, especially regarding the risk of discriminatory outcomes. After analyzing the currently evolving normative data protection framework in Brazil – including the new General Data Protection Act – it discusses whether the existing or suggested legal tools are sufficient to deal with the challenges of automated decision-making processes and their potential asymmetric outcomes.