Regulatory Triggers, Technical Answers: Mapping Laws to Explainable AI Controls in the Brazilian Financial Sector - Vaz, José Eduardo; Oliveira, Pedro Henrique Silva de; Bertoglio, Felipe; Nystrom, Luiz; Kazanowski, Cleber (Anais da Escola Regional de Aprendizado de Máquina e Inteligência Artificial da Região Sul (ERAMIA-RS); 2025: Anais da I Escola Regional de Aprendizado de Máquina e Inteligência Artificial da Região SulDO - 10.5753/eramiars.2025.16786, 2025)
This paper analyzes the regulatory framework for Explainable AI (XAI) in Brazil's financial sector, focusing on the period before the Bill Draft 2.338/2023. We argue that while no unified law on explainability exists, a functional governance structure has emerged through sector-specific regulations from the National Monetary Council (CMN) and the Central Bank of Brazil (BCB). By mapping relevant resolutions, we identify a focus on auditability and risk management in statistical models, rather than a broad right to explanation for consumers. We conclude that Brazil’s evolving AI regulation must reconcile these sectoral rules with a broader, principle-based approach to ensure transparency and protect fundamental rights.