Identifying transaction laundering red flags and strategies for risk mitigation

Abstract

Purpose Transaction laundering has become an increasingly intricate and rampant form of financial misconduct in the age of digital commerce. This research paper conducts an exhaustive examination of this issue, categorizing the various techniques criminals use to highlight areas where existing risk management practices could be further refined. Amid escalating regulatory scrutiny of both financial and nonfinancial entities, the paper stresses the implications of not meeting regulatory standards. As a novel contribution, this study advocates for a shift in risk management strategies. It argues that entities under obligation should harness advanced technological methods to counter transaction laundering challenges effectively. The study serves as a relevant guide for online businesses aiming to strengthen their measures against transaction laundering. For future work, the potential effectiveness of technology-driven countermeasures deserves further scrutiny. Design/methodology/approach This study used a conceptual legal research method, using a library-based doctrinal legal research approach with a conceptual legal perspective, drawing from existing literature. This study reviewed primary and secondary legal sources, including case law and provisions of the Money Laundering (Prohibition) (Amended) Act, 2012, and the Terrorism (Prevention) Act 2013 (as amended). This study also assessed the provisions of the Economic and Financial Crimes Commission (Establishment) Act, Laws of the Federal Republic of Nigeria, 2004. This research further incorporated a blend of archival and secondary legal sources. This study conducted comparative analyses, examining the legal frameworks of Canada, the UK, Hong Kong and China alongside Nigeria to identify potential lessons for enhancing Nigeria’s legislation concerning money laundering and terrorism financing. This study also assessed problems and derived insights from the study’s findings. This research method was chosen to establish the credibility of the findings regarding the issues of money laundering and terrorist financing. Findings The analysis uses a comprehensive network dataset, encompassing ties among individuals and businesses in the Netherlands from 2005 to 2019. It integrates administrative data, including family ties, shared bank accounts and employment history, with corporate information and ownership relations from the Chamber of Commerce. Criminal data related to police interventions, legal convictions and suspicious money laundering transactions are linked to these networks. This unique approach overcomes the scarcity of large empirical datasets in criminological research, offering valuable insights into criminal network behavior and dynamics. Understanding how criminal networks adapt to anti-money laundering policies aids regulatory authorities in designing more effective and efficient measures while also enhancing the tools available to enforcement authorities for detection and investigation. Originality/value AML policies are often criticized for their high costs relative to the perceived benefits. This paper's method avoids dark number estimations and relies on high-quality administrative data. The theoretical contribution includes an examination of specialization, competition and collaboration within criminal networks. The empirical aspect uses a unique dataset and emerges as a methodology for evaluating the effects of AML policy measures using temporal cluster analysis.