Anti-Money Laundering in the Digital Economy: Institutional, Financial, and Educational Channels

Abstract

This paper aims to address the practical challenge of enhancing the effectiveness of anti-money laundering systems within the context of the digital economy. Specifically, it examines how institutional, financial, and educational channels can be optimised to combat illicit financial activities. This research responds to the growing need for a comprehensive anti-money laundering framework that can adapt to the evolving dynamics of the digital economy, where financial crimes are becoming increasingly sophisticated. A methodological framework is proposed to assess and forecast the effectiveness of these channels, employing the principal component method and Saaty hierarchy analysis. The study incorporates both linear and nonlinear regression models to provide medium-term forecasts for the channels' characteristics and their contribution to anti-money laundering effectiveness. An integral indicator is developed to quantify the impact of these channels in combating illicit financial activities. Historical data are utilised to project trends up to 2025, revealing the expected influence of institutional, financial (investment), and educational channels on the anti-money laundering system. The results indicate that, without targeted interventions, the effectiveness of institutional and financial channels gradually decreases, whereas the educational channel maintains a positive trajectory. This analysis underscores the importance of strengthening institutional frameworks and financial oversight to ensure the sustainability of anti-money laundering measures in the digital economy.