Artificial intelligence in the prevention and repression of money laundering (Revista do Tribunal Regional Federal da 3ª Região, 2026)
Money laundering represents a substantial global threat, with trillions of dollars moved annually. Given the increasing sophistication of criminals and 'hyper-globalization,' traditional methods of prevention and enforcement are proving increasingly ineffective. In this context, the use of artificial intelligence (AI) emerges as a promising tool, capable of processing vast volumes of data and identifying complex patterns in a way unattainable for humans, optimizing transaction monitoring, network analysis, and investigative support in vulnerable sectors, especially in cryptocurrency environments. However, the implementation of AI faces significant ethical, legal, and regulatory challenges, such as algorithmic biases that can lead to discrimination, system opacity ('black box'), complex attribution of legal liability, privacy concerns, and the risk of AI itself being used for illicit purposes. Therefore, this article aims to analyze the use of AI in the prevention and suppression of money laundering, exploring its potential, key applications, and the challenges that must be overcome for this technology to be employed effectively and ethically. To this end, it adopts a deductive approach, based on a qualitative bibliographic and documentary review. It concludes that the full potential of AI requires a robust regulatory and ethical framework, based on the development of explainable AI (XAI), public-private collaboration, and human capacity building. These elements ensure that technology serves financial justice in a transparent, ethical, and responsible manner, optimizing mechanisms for the prevention and suppression of money laundering.
Keywords: artificial intelligence; money laundering; prevention; repression; compliance; algorithmic risk; cryptocurrencies