Viktoriia Hurochkina
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Can AI readiness and strong institutions curb AML risk? Cross-country evidence from panel data
Oxana Kirichok
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Viktoriia Hurochkina
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Gulnara Zhanseitova
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Viktoria Dudchenko
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Pavlo Rubanov
,
Denys Babaiev
,
Serhiy Lyeonov
doi: http://dx.doi.org/10.21511/pmf.14(4).2025.05
Public and Municipal Finance Volume 14, 2025 Issue #4 pp. 56-76
Views: 22 Downloads: 3 TO CITE АНОТАЦІЯType of the article: Research Article
Abstract
As emphasized by the FATF, IMF, and World Bank, technological readiness and institutional quality are increasingly decisive in shaping AML effectiveness. By mitigating money-laundering vulnerabilities, strengthening AI readiness, and enhancing institutional quality, tax collection efficiency can be improved and fiscal leakages reduced. These improvements expand the fiscal space available for national budgets, strengthening the financial foundations of public administration. The study aims to examine the impact of Government AI Readiness on AML risk, measured by the Basel AML Index, and the moderating role of institutional quality as captured by the Rule of Law Index. An unbalanced panel dataset that covers up to 168 countries for 2020–2024 was analyzed using fixed effects and random effects models, with variable transformations applied where necessary. All estimations were performed in R Studio. The results indicate that a one-point increase in the Government AI Readiness Index is associated with a 0.048–0.040 point reduction in the Basel AML Index, while a one-unit increase in log GDP per capita decreases the Basel AML Index by 0.54–0.34 points, holding other factors constant. The interaction term between AI readiness and the Rule of Law Index is positive (0.067–0.072), confirming that the risk-reducing effect of AI readiness diminishes as institutional quality strengthens. These findings support the hypotheses and confirm the complementary roles of technological preparedness and institutional integrity in shaping AML outcomes. Fixed effects analysis reveals structural vulnerabilities in AML in Gabon and China, while Sweden exhibits the lowest residual risk after accounting for AI readiness and institutional strength.Acknowledgment
This article was supported by the Ministry of Education and Science of Ukraine (project No. 0123U101945 – National security of Ukraine through prevention of financial fraud and money laundering: war and post-war challenges).
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