The purpose of this study is to explore the evolving landscape of money laundering (ML) research in emerging economies, identifying key trends, challenges, and future research directions.
The paper adopts bibliometric and systematic literature review approaches to distill the main trends, themes and knowledge gaps in the areas of ML research. This paper analyzed indicators of bibliometrics, keyword co-occurrence network and thematic clustering while identifying evolving patterns in researching ML by analyzing 102 articles indexed in both Scopus and Web of Science.
ML research has taken a quantum leap after 2018. It discusses thematic clusters on the challenges facing developing countries, corruption and its interaction with financial systems, illicit financial flows and the macroeconomic consequences of financial crimes. Globalization, political dynamics and informal financial systems pose other challenges. These findings emphasize adaptive, technology-driven frameworks oriented toward the sustainable development goals.
The research provides a cumulative overview of fragmented studies on ML in emerging economies, thereby bridging the gaps between academic research and policy-making. The paper contributes to the wider understanding of the socio-economic and environmental dimensions of financial crimes and positions ML within the global agenda of equitable development.
