AI and Financial Risk Governance in Emerging Markets: Regulatory Gaps and Structural Exposure in Latin America

Abstract

Artificial intelligence is reshaping credit assessment, fraud detection, payment infrastructure, and systemic risk monitoring across the global financial system. Yet the scholarly literature documenting this transformation is geographically lopsided: bibliometric reviews of AI in financial risk management show research output concentrated in India, China, and the United States, with Latin America occupying a marginal position on the map despite housing some of the fastest-growing instant-payment ecosystems in the world. This monograph addresses that imbalance. It examines how artificial intelligence is being adopted across Latin American banking and financial-supervisory systems, how regulatory frameworks in the region compare to the risk-based approaches emerging in the European Union, the United Kingdom, and the United States, and where structural features specific to the region — high informality, currency volatility, fragmented supervisory capacity, and uneven financial inclusion — create risk-management challenges that frameworks built for advanced economies do not fully anticipate. Drawing on regulatory filings, central bank communications, international financial institution reports, and the existing academic literature, the analysis covers comparative regulation, country-level adoption patterns in Brazil, Mexico, Chile, and Colombia, algorithmic credit scoring in economies with large informal sectors, and systemic-risk questions raised by AI-intensive payment rails such as Brazil's Pix. The monograph closes with policy recommendations and an explicit research agenda, distinguishing throughout between findings supported by direct regional evidence and propositions that remain, honestly, hypotheses for future empirical work.