Exploring Money Laundering: Its Impact On Economic Performance And The Role Of Advanced Technologies In Prevention
- IJLLR Journal
- 8 minutes ago
- 4 min read
Mr. Suryavir Gahlawat, Research Scholar, School of Law, Sushant University, Gurugram, India.
Dr. Anjali Sehrawat, Associate Professor, School of Law, Sushant University, Gurugram, India.
ORCID: 0000-0002-0739-25752*
ABSTRACT:
This study examines the multifaceted issue of money laundering, a financial crime encompassing corruption, tax evasion, and terrorist financing, which poses severe risks to global economic and financial stability. Employing a mixed-method approach, the research first conducts a bibliometric analysis of 1,238 publications retrieved from the Scopus database to identify publication trends, prolific authors, contributing countries, and emerging thematic developments through Biblioshiny tools. In parallel, a qualitative case analysis of high-profile money laundering scandals explores their economic repercussions and assesses the effectiveness of risk-mitigation measures. The results indicates growing scholarly attention to money laundering, with distinct thematic clusters and county level contributions. Citation analysis highlights the influence of prolific authors, while the case analysis underscores how large-scale money laundering activities destabilize national economies and highlight the critical role of advanced technologies in enhancing detection and prevention mechanisms. By integrating bibliometric and qualitative evidence, the study contributes a comprehensive perspective on the evolution of money laundering research, uncovers gaps in the existing literature, and offers recommendations to strengthen global anti-money laundering frameworks.
Keywords: Money Laundering, financial and economic performance, Artificial Intelligence, Anti-money laundering, Bibliometric analysis, Qualitative analysis.
1.0 Introduction:
Money laundering is a complex financial crime, it involves disguising the illicit origins of money generated through illegal activities such as corruption, tax evasion, and terrorist financing (Rusanov and Pudovochkin, 2021). The economic cost of money laundering is immense. It not only distorts financial markets but also reduces foreign direct investment (FDI), hampers tax revenue collection, and erodes public trust in financial systems (Vaithilingam & Nair, 2007). With the emergence of new financial instruments and platforms, especially blockchain and AI-based systems, the modus operandi of money laundering has become increasingly sophisticated (Tiwari et al., 2024). Yet, the academic literature has not adequately kept pace with these evolving patterns, especially in the Indian context where high-profile scandals highlight systemic vulnerabilities. Moreover, money laundering undermines economic stability and increasingly exploits technological advancements such as blockchain and AI-based systems, which have significantly transformed the methods used to obscure financial trails (Tiwari et al., 2024). Despite these evolving threats, the research landscape and prevention strategies remain underexplored, particularly within the Indian context, where recent high-profile scandals reveal deep systemic vulnerabilities. This study is therefore motivated by the urgent need to address these economic and technological dimensions of money laundering and to bridge existing gaps in academic and policy-oriented research. To bridge this gap, the present study adopts a hybrid methodology-combining bibliometric analysis with qualitative case studies, to map the evolving research trends and real-world impact of money laundering. The inclusion of qualitative case analysis is essential because it complements bibliometric trends by analysing how real-world money laundering scandals expose systemic loopholes and deeper understanding of the economic repercussions and evaluate the effectiveness of anti-money laundering measures in practices. This integration ensures that the research not only identifies thematic gaps in the literature but also connects them to lived realities, thereby strengthening both academic and policy relevance.
The first part of the study analyses 1,238 research papers retrieved from Scopus (2009–2024) using Biblioshiny, identifying publication trends, key themes, leading authors, countries, and journals. The second part incorporates qualitative case studies of prominent Indian high-profile money laundering cases, such as the PNB scam and INX Media scandal, to map trends and evaluate their economic impacts.
The study addresses the following research questions (RQs), each targeting an important gap in the existing literature:
RQ1 address the lack of systematic reviews on emerging trends and research focuses in the domain of money laundering between 2009 to 2024 (Ahuja et al., 2023)
RQ2: What are the leading authors and leading countries contributing in the area of money laundering.
RQ3: What is the most frequent word cloud used in the research articles and how the word evolves into the money laundering?
RQ4. What are the citation analysis and what are the author’s contribution to the journals?
RQ5: What are the evolving themes surrounding money laundering?
RQ5: What are the gaps and potential research directions in the context of money laundering. (Zolkaflil et al., 2019)
The bibliometric findings of the study suggest that academic research predominantly centers on anti-money laundering (AML) compliance, cryptocurrency, and regulatory gaps in emerging economies, while case studies highlights the regulatory loopholes in India’s banking and FDI system. Moreover, this study makes a novel contribution by being the first to integrate bibliometric and qualitative methods to analyze both the academic and practical dimensions of money laundering’s impact on national economies, particularly in India. The findings not only enrich academic discourse but also inform policymakers about the urgent need for technology-driven AML frameworks, including the use of AI, blockchain, and machine learning tools to strengthen preventive and enforcement mechanisms. The structure of the present article is organized as follows: The first section highlights the introduction and background information, which is followed by comprehensive review of relevant literature. The thirds section of the study primarily outline the research methodology and outcome of the study. Lastly the paper concludes by discussing the main insights derived from the results, that provides implication and directions for future research.
The structure of the present paper is organized as follows: the first section presents the introduction, followed by a comprehensive review of relevant literature. The third section primarily outline the research methodology and highlights the key findings of the study. Lastly, the paper concludes by explaining the main insights derived from the results, that provides implications and directions for future research and practice.
