Money Laundering in Crypto-Asset Environments: A Systematic Literature Review

This article provides a systematic literature review of recent research on money laundering in crypto-asset environments, focusing on the main operational challenges and technical solutions proposed. Following PRISMA 2020 guidelines, the review draws on searches in Web of Science, Scopus and Google Scholar, which identified 680 records and led, after screening and the application of inclusion and exclusion criteria, to a final sample of 58 academic studies published between 2020 and 2025. The review identifies four core challenges in blockchain-based anti-money laundering: pseudonymity, label scarcity and class imbalance, structural and computational complexity, and cross-blockchain data fragmentation. In response, the literature proposes several detection approaches, particularly feature-based and graph-based models, focusing on transactions, addresses, mixers and service providers. The findings show that, although these methods improve the detection of suspicious activity, important limitations remain regarding real-world identity attribution, reliable AML-specific ground-truth labels, scalability, operational validation and cross-chain flow reconstruction. The article contributes an analytical framework that links structural AML challenges with methodological responses, supporting clearer comparison of models and identifying priorities for future research. It also highlights the need for multidisciplinary collaboration across data science, finance, regulation, economics and forensic investigation.