Determinants of anti-money laundering system’s effectiveness in Ukraine: Insights from factorial and regression analysis

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The effectiveness of anti-money laundering systems is vital for national economic resilience, especially in transitional economies facing wartime challenges, such as Ukraine. This study aims to identify key managerial determinants of the effectiveness of Ukraine’s anti-money laundering and counter-terrorist financing (AML/CFT) system and to develop evidence-based recommendations for improving its performance. Based on data from Ukrainian national institutions for the period 2011–2023, the study employs principal component analysis and multiple linear regression to evaluate 44 statistical indicators related to institutional workload, procedural efficiency, and inter-agency coordination. The findings reveal that a small set of indicators, including the volume of suspicious transaction reports from non-banking institutions, the number of dossiers compiled, and the backlog of unresolved judicial cases, explain over 70% of the system’s output variance. The final model exhibits high explanatory power (R² = 0.963), underscoring the importance of prioritizing high-impact operational metrics. The study concludes that targeted procedural reforms and enhanced coordination between institutions can significantly strengthen AML/CFT outcomes in fragile and reforming contexts.

Acknowledgment
This study 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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    • Figure 1. Scree plot – Graphical visualization of principal components
    • Figure 2. Pareto diagrams of factors significantly affecting the effectiveness of Ukraine’s AML/CFT system
    • Figure 3. Pareto diagrams showing the significance of key factors affecting the effectiveness of Ukraine’s AML/CFT system
    • Figure 4. Normal distribution of residuals from the regression model explaining the effectiveness of Ukraine’s AML/CFT system
    • Figure 5. Normal distribution of residuals from the final regression model of Ukraine’s AML/CFT system effectiveness
    • Table 1. Eigenvalue matrix – Tabular representation of principal components
    • Table 2. Summary of interim calculations for determining weight coefficients of indicators of Ukraine’s AML/CFT system with estimated values of weight coefficients
    • Table 3. One-factor test for the significance of selected indicators affecting the effectiveness of Ukraine’s AML/CFT system
    • Table 4. Characteristics of adequacy and accuracy of the model
    • Table 5. Regression analysis of key factors influencing the effectiveness of Ukraine’s AML/CFT system
    • Table 6. Regression analysis results for the most statistically significant factors affecting the effectiveness of Ukraine’s AML/CFT system
    • Table A1. Indicators reflecting the activities of key institutions involved in Ukraine’s AML/CFT system
    • Table A2. Input statistical base for research into the activities of Ukraine’s AML/CFT system
    • Table A3. Factor loadings– Intermediate calculations
    • Table A4. One-factor significance test of factors influencing the effectiveness of Ukraine’s AML/CFT system
    • Table A5. Correlation matrix of interdependence of factors of Ukraine’s AML/CFT system
    • Conceptualization
      Dariusz Krawczyk, Gulnara Zhanseitova, Oleksii Zakharkin, Maksym Zhytar, Tetiana Dotsenko, Ievgenii Vovk, Tetiana Vasylieva
    • Funding acquisition
      Dariusz Krawczyk
    • Resources
      Dariusz Krawczyk
    • Writing – original draft
      Dariusz Krawczyk, Gulnara Zhanseitova, Oleksii Zakharkin, Maksym Zhytar, Tetiana Dotsenko, Ievgenii Vovk, Tetiana Vasylieva
    • Writing – review & editing
      Dariusz Krawczyk, Gulnara Zhanseitova, Oleksii Zakharkin, Maksym Zhytar, Tetiana Dotsenko, Ievgenii Vovk, Tetiana Vasylieva
    • Visualization
      Gulnara Zhanseitova, Tetiana Vasylieva
    • Validation
      Oleksii Zakharkin, Tetiana Vasylieva
    • Software
      Maksym Zhytar, Tetiana Vasylieva
    • Formal Analysis
      Tetiana Dotsenko, Tetiana Vasylieva
    • Data curation
      Ievgenii Vovk, Tetiana Vasylieva
    • Investigation
      Tetiana Vasylieva
    • Methodology
      Tetiana Vasylieva
    • Project administration
      Tetiana Vasylieva
    • Supervision
      Tetiana Vasylieva