Money laundering (ML) is harmful as it provides an opportunity for criminals to launder (or legitimise) criminal proceeds and reinvest laundered funds into their activities. ML also creates economic distortions, erosion of financial sectors, reduced government revenue and other socioeconomic effects. To reduce potential ML, governments use security intelligence and financial regulation. To enhance financial security and reduce the illicit ML opportunities, countries will benefit from understanding how the adoption of the Financial Action Task Force (FATF) Recommendations and their regulatory affiliations affect the risk of ML. Our findings reveal irregularity in the guidelines used by countries to develop AML regulatory policy, which undermines AML security. Further, highly FATF-compliant countries tend to enjoy lower ML risk and are often affiliated with well-established regulatory groups. This suggests the need to maintain ongoing and consistent compliance standards across all affiliation groups and further facilitate cross-jurisdictional cooperation among financial intelligence agencies to maximise the spillover effect from highly compliant and low ML-risk jurisdictions.

洗钱 (ML) 是有害的，因为它为犯罪分子提供了洗钱（或合法化）犯罪收益并将洗钱资金再投资于其活动的机会。ML 还会造成经济扭曲、金融部门侵蚀、政府收入减少和其他社会经济影响。为了减少潜在的机器学习，政府使用安全情报和金融监管。为了加强金融安全并减少非法机器学习机会，各国将受益于了解金融行动特别工作组 (FATF) 建议的采用及其监管机构如何影响机器学习的风险。我们的调查结果揭示了各国用于制定反洗钱监管政策的指南存在违规行为，这破坏了反洗钱安全。更远，高度符合 FATF 的国家往往享有较低的 ML 风险，并且通常隶属于完善的监管团体。这表明需要在所有附属团体中保持持续和一致的合规标准，并进一步促进金融情报机构之间的跨辖区合作，以最大限度地发挥高度合规和低 ML 风险辖区的溢出效应。