Anti-money Laundering Framework Research Articles

How do Ivorian Cyberfraudsters Manage Their Criminal Proceeds?

AbstractThis article delves into the intricacies of managing illicit financial gains among Ivorian cyberfraudsters, shedding light on the findings of a field study conducted in Côte d’Ivoire by Swiss and Ivorian research teams. The study involved interviews with cybercriminals, law enforcement officials, and subject matter experts, in order to answer a specific question: What strategies do Ivorian cyberfraudsters use to manage and launder the criminal proceeds originating from romance scams and sextortion? The results explore the tactics employed by cyberfraudsters to obfuscate the illicit financial flows, their organizational structures, and the strategies they employ in managing and using their gains. It confirms certain elements from the scientific literature, in addition to introducing new insights for a better understanding of the processes of money laundering and the use of illicit funds. The article also unravels the multifaceted challenges encountered within the anti-money laundering framework in the context of cybercrime and raises avenues for further reflection and future work to enhance the fight against this scourge.

Money laundering prevention in the digital age: Leveraging graph databases for effective solutions

As financial transactions increasingly migrate to the digital realm, the challenge of preventing money laundering has become complex (Ramada, 2022). The research presented in this paper explores innovative approaches to combating money laundering in the digital age, focusing on the application of graph databases as a powerful tool for effective solutions. The study deep dives into the capabilities of graph databases in modeling intricate relationships within financial networks, conducting network analysis, and detecting anomalies in transaction patterns. By leveraging these capabilities, financial institutions can enhance customer due diligence, monitor transactions in real-time, and visualize complex networks to uncover hidden connections indicative of money laundering activities. The paper contains examination of case studies, regulatory compliance considerations, and the integration of graph databases into existing anti-money laundering frameworks. Ultimately, objective of this research has been to contribute to the evolving landscape of money laundering prevention strategies by highlighting the potential of graph databases as a key technology in the digital age.

Gravitating towards Artificial Intelligence on Anti-Money Laundering A PRISMA Based Systematic Review

In Bangladesh, like many other countries, the implementation of Anti-Money Laundering (AML) measures plays a crucial role in the fight against financial offences and the maintenance of the financial system's integrity. The integration of Artificial Intelligence (AI) is one of the technologies for AML that has emerged as a promising approach to enhance the detection and prevention of financial crimes. The researcher aims to investigate the current state of AML, the impact of AI, the roles involved, and the legislation to achieve economic stability for the transformation of Bangladesh into a smart nation by 2041. In this systematic review study, the PRISMA framework is utilized to provide a comprehensive analysis of existing literature on the application of AI in AML, with a focus on risks, laws, and implications, particularly within the context of Bangladesh. The review synthesizes findings from diverse sources (Web of Sciences, Scopus, PubMed, and DOAJ indexing articles and reports) including academic research, industry reports, and regulatory documents, to assess the effectiveness, challenges, and ethical considerations associated with AI-driven AML solutions. Through a structured search strategy and rigorous selection criteria, the researchers discovered a total of 299 research papers, consisting of 181 latest studies and 117 previous relevant studies identified and analyzed to elucidate key trends, methodologies, and gaps in the current landscape of AI-enabled AML practices. The review also offers insights and recommendations for policymakers, practitioners, and researchers interested in leveraging AI technologies to combat money laundering effectively while navigating regulatory frameworks and safeguarding privacy rights. By critically examining the intersection of AI, AML, and legal frameworks, this study contributes to the ongoing discourse on the role of technology in addressing financial crime challenges in Bangladesh and beyond.

Integrating Machine Learning in Anti-Money Laundering through Crypto: A Comprehensive Performance Review

The integration of machine learning (ML) algorithms in Anti-Money Laundering (AML) practices has garnered significant attention due to its potential to enhance the detection and prevention of illicit activities in the cryptocurrency ecosystem. This systematic literature review analysed the effectiveness of integrating ML algorithms in detecting and preventing crypto laundering activities, identify the most frequently used ML algorithms, examine trends in publication and research methodologies, and discuss key challenges and constraints associated with integrating ML technologies into AML frameworks. A comprehensive search strategy was employed to identify relevant studies, resulting in the inclusion of 52 articles published between 2019 and 2023. The findings reveal a growing interest in the field, with a notable increase in publications in recent years. Traditional ML models such as Logistic Regression, Random Forest, and Support Vector Machine (SVM) remain prevalent, while deep learning models like Multilayer Perceptrons (MLP) and Long Short-Term Memory (LSTM) networks are gaining popularity. Graph Convolutional Networks (GCNs) have emerged as a significant area of exploration, particularly in the context of graph data analysis in cryptocurrencies. Despite advancements in ML, cryptocurrencies continue to pose a high risk of money laundering due to the practical challenge of implementation ownership of the various ML models. Future research should focus on how these challenges will be addressed to ensure the effective and sustainable use of ML technologies in real-world AML practices.

Money Laundering Prevention through Regulatory Technology and Internal Audit Function in Indonesia Banking Sector

Money laundering poses a significant challenge globally, involving using cash to conceal the origins of funds. With the rise of digitalisation and the adoption of financial technology (FinTech), the financial sector has been compelled to adapt to these changes. The COVID-19 pandemic has further accelerated the use of FinTech services, including digital banking, to address social distancing concerns and enhance customer convenience. Despite having an index of risk considered moderate for money laundering, Indonesia continues to be a destination for these types of illegal activities. Anti-money laundering (AML) and counter-terrorism financing (CFT) programs must be implemented, especially in all financial service providers that Bank Indonesia oversees.Additionally, the internal audit function is crucial in identifying money-laundering activities within banks. However, there needs to be more research regarding integrating RegTech and evaluating internal audit functions in preventing money laundering in Indonesian banks. This paper aims to address this gap by examining the benefits of RegTech solutions and the role of internal audit functions in preventing money laundering. The findings can be used to enhance regulations and implement effective measurement to combat money laundering and illicit activitivities. Furthermore, the study highlights the importance of Indonesia's membership in the Financial Action Task Force (FATF) to strengthen the country's AML framework and contribute to global policies on AML and countering the financing of terrorism.

Virtual assets and the prevention of money laundering: a critical and comparative analysis of the laws of Mauritius, Japan and South Africa

PurposeDue to their particular nature, virtual assets (VA) are vulnerable to financial crimes such as money laundering and if the appropriate legal mechanisms are not established, this may result in the financial collapse of various economies. To this effect, best practices and standards have been published by some international organisations such as the Financial Action Task Force and IMF which are now domesticated in the national laws of several countries. Therefore, the purpose of this study is to analyse the anti-money laundering (AML) legislative framework in the context of VA in three countries, namely, Mauritius, Japan and South Africa.Design/methodology/approachTo achieve the research objective, the Mauritian AML laws in the context of VA were compared with the corresponding laws of some other countries, namely, Japan and South Africa. As such, a qualitative research method was adopted. In particular, the black letter approach was used to examine the relevant laws of these countries. A comparative analysis was conducted concerning the relevance of AML laws for each country when dealing with VA with the view of suggesting recommendations for Mauritian stakeholders to adopt to enhance the existing AML legal and regulatory framework.FindingsThe comparative study conducted has revealed that there are both similarities and divergences among the AML framework of the three countries further to which this research recommends that the Mauritian laws must be amended concerning the duration of information storage on VA, the definition of VA, advertisement by VA service providers and the electronic submission of annual reports. The Mauritian regulatory bodies also need to play a more active role in their joint collaboration to monitor suspicious VA transactions to combat money laundering.Originality/valueAt present, this study will be among the first academic writings on the efficiency of AML laws in the context of VA in Mauritius and also, because existing literature is quite scarce on assessing the adequacy of AML legislation in developing countries, this research aims at filling in the gap in literature. This study is carried out with the aim of combining a large amount of empirical, theoretical and factual information that can be of use to various stakeholders and not only to academics.

Towards Learning to Discover Money Laundering Sub-network in Massive Transaction Network

Anti-money laundering (AML) systems play a critical role in safeguarding global economy. As money laundering is considered as one of the top group crimes, there is a crucial need to discover money laundering sub-network behind a particular money laundering transaction for a robust AML system. However, existing rule-based methods for money laundering sub-network discovery is heavily based on domain knowledge and may lag behind the modus operandi of launderers. Therefore, in this work, we first address the money laundering sub-network discovery problem with a neural network based approach, and propose an AML framework AMAP equipped with an adaptive sub-network proposer. In particular, we design an adaptive sub-network proposer guided by a supervised contrastive loss to discriminate money laundering transactions from massive benign transactions. We conduct extensive experiments on real-word datasets in AliPay of Ant Group. The result demonstrates the effectiveness of our AMAP in both money laundering transaction detection and money laundering sub-network discovering. The learned framework which yields money laundering sub-network from massive transaction network leads to a more comprehensive risk coverage and a deeper insight to money laundering strategies.

The Place and The Role of Financial Monitoring in Anti-Money Laundering System

Financial monitoring plays a pivotal role in the overall effectiveness of an anti-money laundering (AML) system. This article explores the place and role of financial monitoring in preventing and detecting money laundering activities. The authors highlighted the significance of effective financial monitoring in meeting regulatory compliance requirements. The definition of the role and place of financial monitoring in the fight against the legalisation of corruption proceeds are updated, considering the tasks and requirements set before Ukraine as a candidate country for the European Union and the challenges caused by the state of war. The article aims to analyse and provide an understanding of the importance of financial monitoring in the broader context of combating money laundering. The authors used different methods and approaches depending on the nature of the research, such as literature review, legal and doctrinal analysis, and comparative analysisб dialectical method, method of analysis and synthesis and method of terminological analysis. The findings of this research underscore the criticality of financial monitoring in safeguarding the integrity of the financial system and protecting economies from the harmful effects of money laundering. By understanding the place and role of financial monitoring within the broader AML framework, financial institutions, policymakers, and regulators can enhance their efforts to combat money laundering and ensure a safer and more secure economic environment.

A systematic review of anti-money laundering systems literature: Exploring the efficacy of machine learning and deep learning integration

Money laundering is a complex issue with global impact, leading to the increased adoption of artificial intelligence (AI) to bolster anti-money laundering (AML) measures. AI, with machine learning and deep learning as key drivers, has become an essential enhancement for AML strategies. Recognizing this emerging trend, this study embarks on a systematic literature review, aiming to provide novel insights into the implementation, effectiveness, and challenges of these sophisticated computational techniques within AML frameworks. A critical analysis of 26 selected studies published from 2018 to 2023 highlights the essential role of machine learning and deep learning in identifying money laundering schemes. Notably, the decision tree algorithm stands out as the most commonly utilized technique. The combined use of both learning models has proven to significantly increase the effectiveness of AML systems in detecting suspicious financial patterns. However, the optimization of these advanced methods is still constrained by issues related to data complexity, quality, and access.

An overview of anti-money laundering practice in the indian financial system

Money laundering is a menace to economies and a central concern globally. The financial system remains the primary target of money launderers. While the risk of money laundering cannot be entirely eliminated, it can be mitigated through specific preventative measures. In this regard, FATF took its initial international step by presenting its 40 recommendations to combat Money Laundering and Terrorist Financing. These recommendations have since evolved into a model for successful national and global Anti Money Laundering and Countering Financing of Terrorism (AML/CFT) controls. This paper aims to assess and describe the anti-money laundering (AML) practice and framework within the Indian financial system, as well as to examine how the Indian financial system has addressed FATF's recommendations on AML. The study utilizes secondary data obtained from books, annual reports, and selected websites to achieve its objectives. The findings of the study demonstrate that the Anti-Money Laundering (AML) regime in the Indian financial system is regulated by the Prevention of Money Laundering Act (PMLA) along with an established regulatory and supervisory framework to address FATF Recommendations. The AML framework of the Indian financial system includes FIU-India, which operates as a national agency for receiving, processing, analyzing, and disseminating information related to suspicious transactions. Additionally, the Reserve Bank of India (RBI), Securities Exchange Board of India (SEBI), and Insurance Regulatory Development Authority (IRDA) serve as the regulatory and supervisory bodies for financial institutions in India. Regulating, supervising, and developing Anti-Money Laundering (AML) policies and practices for the Indian financial sector fall under the responsibilities of these three authorities.

Policy Brief 10: Using anti-money laundering frameworks to fight illegal wildlife trade in Uganda

In February 2020, Uganda made a high-level political commitment to work with the Financial Action Task Force (FATF) and Eastern and Southern Africa Anti-Money Laundering Group (ESAAMLG) to strengthen the effectiveness of its anti-money laundering (AML) regime. Among other commitments, Uganda undertook to demonstrate that law enforcement agencies and judicial authorities apply the money laundering offence consistent with the identified risks. 
 Studies show that Uganda has high risks for cross-border movement of illegally obtained wildlife and wildlife products, both as a source and transit country. In addition, Uganda and the East African region in general have made some massive seizures of illegal wildlife products, which points to organised criminal activity. Notably, no money laundering prosecutions have to date arisen out of illegal wildlife trade (IWT) as a predicate offence in Uganda, Kenya and Tanzania.
 This short Policy Brief provides an outline of how the AML framework (intelligence, investigations and prosecutions) can be utilised to help combat IWT and the corruption that facilitates it. The insights are drawn from the Ugandan context, but can be applied with appropriate adjustments to other jurisdictions seeking to strengthen efforts to combat IWT and related corruption/money laundering.

The European anti-money laundering framework – At a turning point? The role of financial intelligence units

Last July, 2021, the European Commission presented a package of legislative proposals that aspires to radically change the EU anti-money laundering legal framework. This paper focuses on Financial Intelligence Units (FIUs) role and functions, and critically analyses the impact of on-going developments, taking into account international standards and the most recent studies and research. The overall conclusions show that many shortcomings remain and, in particular, how the accelerator is pushed excessively in the direction of increasing powers and too little in that of guarantees of FIUs independence and autonomy and of protection of individual rights.

Rethinking anti-money laundering supervision: The Single Supervisory Mechanism - a model for a European anti-money laundering supervisor?

Whereas the prudential supervision of credit and other financial institutions has been a core policy concern of the EU legislator in the aftermath of the 2008 Financial Crisis, the supervision of private sector entities within the European Anti-Money Laundering framework has been subject to less attention. However, on 20 July 2021, the European Commission intervened and published legislative proposals for two regulations and one directive, meant to boost the European response to the phenomenon of Money Laundering. This contribution – after having pointed out the shortcomings of the current legislative framework – pursues a twofold objective: first, offering an in-depth analysis of whether the Single Supervisory Mechanism, set up within the banking union for the purposes of prudential supervision, might be a useful precedent of Europeanisation to build up upon in matters of Anti-Money Laundering supervision, and second, commenting the possible approaches to be taken when setting up an EU level Anti-Money Laundering supervisor. The systemic cross-border importance of AML – beyond the euro area – warrants the establishment of a new EU agency specialised on AML, invested with more supervisory powers than EBA, ESMA and EIOPA and taking over the direct supervision of high-risk obliged entities, while indirectly supervising the remaining entities. It is argued furthermore that such institutional reform should necessarily be accompanied by the establishment of a Single Rulebook, which enjoys direct applicability across the EU.

A critical analysis of the anti-money laundering legal and regulatory framework of Mauritius: a comparative study with South Africa

PurposeIndeed, the value of money laundering globally is between 2% and 5% of the world’s gross domestic product, which represents $800bn to $2tn per year. There is therefore a dire and urgent need to curb money laundering offences at both national and international level. As such, the purposes of this research are to critically analyse the anti-money laundering (AML) laws and regulations of Mauritius, to identify loopholes in inherent in the Mauritian system and to suggest recommendations to enhance the AML laws in the country.Design/methodology/approachTo achieve these research objectives, the study will adopt the black letter methodology by analysing laws and regulations on AML of Mauritius and will also conduct a comparative analysis against the corresponding AML laws of South Africa. In fact, South Africa has been selected for the comparison to assess how Africa’s most powerful economic powerhouse is dealing with issues of money laundering and whether Mauritius may implement some of these measures to enhance its legal and regulatory framework on AML.FindingsThe research sets out a comprehensive view on the AML legislative framework of South Africa and Mauritius. It has highlighted the mechanisms used in these two countries to combat money laundering is the risk-based approach. Finally, recommendations have been proposed to improve the existing AML frameworks of Mauritius and which can further protect the financial system of the country. However, these suggestions will depend on the evolution of financial crimes within and outside the jurisdiction, and ongoing amendments will always be required to rigidly protect Mauritius from money launderers.Originality/valueAt present, to the best of the authors’ knowledge, this study will be amongst the first academic writings on the effectiveness of the legal and regulatory measures undertaken by the Mauritian authorities to deal with AML crimes in the country. The study is carried out with the aim of combining a large amount of empirical, theoretical and factual information that can be of use to various stakeholders and not only to academics.

The anti-money laundering framework for precious stones and metals dealers in Singapore

PurposePrecious stones and metals have commonly been used throughout the world as a conduit for terrorism and money laundering activities. Such illicit use of these assets has called for its much-needed attention from a regulatory perspective. This is particularly relevant in a financial haven such as Singapore. Accordingly, the purpose of this paper is to explore how several of the most common trading and investment activities involving precious stones and metals in Singapore are regulated.Design/methodology/approachThe research explores activities include the trading of – the storing or custodising of – and the current available savings plans involving the use of precious stones and metals. It is based mainly on information collected from various legal sources such as books, domestic legislation and international papers issued by the Financial Action Task Force and the Asia Pacific Group on Money Laundering.FindingsWith the author’s findings, the analysis may prove useful for businesses seeking to navigate the regulatory landscape for precious stones and metals in Singapore, for investors seeking to understand the protection offered to them under the regulatory framework and for other jurisdictions seeking to evaluate and refine their existing framework for regulating precious stones and metals.Originality/valueTo the author’s knowledge, this is the first substantive academic study which analyses the regulatory landscape for the use of precious stones and metals under the Singapore Law.

The Single Supervisory Mechanism (SSM) and the EU Anti-Money Laundering framework compared: governance, rules, challenges and opportunities

The Single Supervisory Mechanism (SSM) and the EU Anti-Money Laundering framework compared: governance, rules, challenges and opportunities

Intelligence and Corruption

The Journal of Intelligence, Conflict, and Warfare is pleased to publish the following thought piece from one of our esteemed Speakers from the 2020 West Coast Security Conference. The author, Mr. Dalip, is a lawyer working in the financial crime and corruption sphere. From 2015 to 2018, Mr. Dalip was a chairman at the Steering Group Planning Committee for the Caribbean Financial Action Task Force (CFATF); and from 2014 to 2018, he was a special legal advisor to the Ministry of Attorney General Trinidad and Tobago. The intersection between corruption and intelligence is gaining increased focus. Foreign intelligence services have an anti-corruption role at the strategic level through Intelligence Risk Assessments and at the operational level during post-conflict operations. Intelligence assessments of the effectiveness of non-kinetic tools on target countries also guide implementation and policy changes. The roles of security intelligence and foreign intelligence services are, however, no longer always discrete, particularly in the context of non-state actors. Foreign intelligence services would benefit from the skill sets of security intelligence agencies in detecting corruption related predicate offences, both in performing their core roles and supporting law enforcement operations. This includes the use of financial intelligence as well as other key open source intelligence resulting from anti-money laundering frameworks, the development of which has been driven globally by the Financial Action Task Force. In performing these roles, intelligence agencies must also be mindful of their own vulnerability to corruption.

How Trinidad and Tobago's Anti-Money Laundering Framework Affects Its Commercial Operations

A paper interrogating the direct and indirect effect of Trinidad and Tobago's anti-money laundering regime on its commercial banking operations and the resulting tension between the bank's civil duties and obligations to its customers and the public duty imposed by anti-laundering legislative frameworks to stop money laundering. The paper also considers the strategic deficiencies within Trinbago's anti-laundering regime.

An Intelligent and Secure Framework for Anti-Money Laundering

This paper aims to secure money transactions due to money laundering crimes. It presents a Secure Intelligent Framework for Anti-Money Laundering (SIFAML). This framework is new and includes two main processes. In addition, it supports several modules. The first process is the monitoring process for detecting possible ML. The second process is a STRIPS-based planning process that targets strengthening the belief in the potential problems detected in the monitoring process. In addition, STRIPS is a hierarchical planning technique that makes utilization of the means-ends tactic, by finding the goal in the root of the hierarchical. It searches gradually for the plan services that can diminish the distinction between the current state and the goal. An important feature of SIFAML is the integration of the planner and the OWL-'s reasoner. This means that the reasoner might do the entire planner’s interactions with a particular state. In addition, SIFAML contains several supporting modules for data gathering and mediation, link analysis, and risk scoring. To present the applicability of SIFAML, it has been discussed using different instances. This work provides an analytical study and a comparison between the performance and capabilities of SIFAML and other related works are given and the concluding remarks are discussed. The proposed framework improves the discovery of ML and reduces false-positive alarms. It moves anti-money laundering frameworks to make use of an intelligent formalism by using ontology and STRIPS-based planning. Finally, this work introduces SIFAML as a novel ontology-based and plan-based system for AML frameworks.

Is there a commendable regime for combatting money laundering in international business transactions?

Purpose Money laundering and grand business corruption continue to plague the global economy, accounting for 2%-5% of the global gross domestic product. Illicit funds, produced through grand corruption, are laundered using complex layering schemes that cloak them in legitimacy by concealing their origins. Lamentably, weak anti-money laundering (AML) frameworks promote economic instability, unjust commercial advantages and organized crimes. This study aims to highlight the need for comprehensive anti-corruption and AML frameworks by critiquing the exploitable gaps in the global AML regime created by heterogeneous state-level AML regimes to date. Design/methodology/approach This study welcomes the United Nations Convention against Corruption (UNCAC) and the financial action task force (FATF) recommendations but underscores the limitations of their effectiveness by investigating state-level enforcement mechanisms to determine these instruments’ true impact or lack thereof. The mutual evaluation reports (MERs) and state-level AML regimes in the UK, the USA and Canada are analyzed to illustrate the distinct implementation of international soft law in domestic legislation. Findings This study finds that UNCAC and the FATF recommendations are pivotal steps towards the establishment of a global AML regime for international business, albeit, one that remains imperfect because of the inconsistency of state-level AML frameworks. Consequently, international cooperation is needed to navigate and improve the discrepancies in varied AML legislation. Originality/value The author provides an in-depth and balanced analysis of current state-level AML developments and relies upon the recent 2016-2018 MERs to indicate the successes and flaws of various AML legislation. Therefore, this critique may guide stakeholders to construct robust AML frameworks and contributes to academic research in AML.