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

Anton Boyko (), Andrew Zimbroff (), Serhii Mynenko () and Yang Chen ()
Additional contact information
Anton Boyko: Sumy State University, Sumy, Ukraine
Andrew Zimbroff: College of Education and Human Sciences, University of Nebraska-Lincoln, Lincoln, USA
Serhii Mynenko: Sumy State University, Sumy, Ukraine
Yang Chen: Fujian Normal University, Fuzhou, China

Virtual Economics, 2024, vol. 7, issue 3, 59-80

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.

Keywords: anti-money laundering; institutional channel; investment channel; tax channel; educational channel; Saati hierarchy analysis method; forecast integral indicator (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.virtual-economics.eu/index.php/VE/article/download/360/167 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aid:journl:v:7:y:2024:i:3:p:59-80

DOI: 10.34021/ve.2024.07.03(4)

Access Statistics for this article

Virtual Economics is currently edited by Aleksy Kwilinski

More articles in Virtual Economics from The London Academy of Science and Business
Bibliographic data for series maintained by Aleksy Kwilinski ().