METHODOLOGIES FOR COUNTRY RISK ASSESSMENT IN AML/CFT: A COMPARATIVE ANALYSIS OF POLICY FRAMEWORKS AND ECONOMETRIC MODELS

Assessing country risk in Anti-Money Laundering and Counter-Terrorist Financing (AML/CFT) is increasingly significant in global financial integration, digitalisation, and persistent illicit financial flows. Despite international standards, the unobservable nature of laundering makes risk measurement highly dependent on proxies and methodological choices, creating both conceptual and practical challenges. This research aims to conduct a comparative analysis of AML/CFT country risk assessment methodologies, integrating policy frameworks with econometric and probabilistic models. The study employs a comparative analytical framework, synthesising official assessments (FATF mutual evaluation reports, NRAs, and IMF/World Bank tools), quantitative indexes (e.g., Basel AML Index), econometric approaches (Walker-Unger gravity model, Ferwerda’s black box, Schneider-Windisch MIMIC), qualitative frameworks, and emerging Bayesian/probabilistic methods. The findings indicate that no single methodology provides a definitive measure of country risk. Policy-driven tools ensure global legitimacy and comparability but are static, resource-intensive, and sometimes politicised. Composite indices and proprietary models offer usability and accessibility but often lack methodological transparency and risk oversimplification. Academic econometric approaches generate quantitative estimates and enhance analytical depth, though they remain sensitive to assumptions and limited in operational application. Probabilistic and Bayesian methods represent a promising frontier, explicitly incorporating uncertainty and diverse data sources, but their complexity and reliance on subjective priors constrain widespread adoption.