Illicit Funds Research Articles

Combating terrorist financing in cryptocurrency platforms: The role of AI and machine learning

This study addresses the critical issue of terrorist financing through cryptocurrency platforms, a growing concern due to digital currencies' pseudonymous nature and global reach. The research explores the strategic role of Artificial Intelligence (AI) and Machine Learning (ML) in identifying, preventing, and disrupting the flow of illicit funds used to finance terrorism. Employing a mixed-methods approach, the study integrates qualitative case studies of documented instances of cryptocurrency-based terrorist financing with quantitative data analysis from significant cryptocurrency exchanges. Advanced AI and ML algorithms, including supervised learning models such as decision trees and neural networks, were applied to detect suspicious transactions indicative of terrorist activities. The findings reveal that AI and ML technologies significantly enhance the ability to identify patterns of terrorist financing within large and complex datasets, with models achieving precision and recall rates exceeding 90%. However, challenges remain, particularly regarding the quality and standardization of data across platforms, algorithmic biases, and the need for continuous updates to counter evolving tactics used by terrorist organizations. The study concludes that AI and ML present powerful tools for enhancing financial security. However, their successful implementation requires overcoming these challenges through collaborative efforts among stakeholders, including financial institutions, regulators, and technology providers. This research contributes to the growing field of economic crime prevention by offering a robust framework for integrating AI-driven solutions into the fight against terrorist financing on cryptocurrency platforms.

Immigrants and innovators: financial inclusion and the ‘de-banking’ of the digital asset industry

ABSTRACT ‘De-banking’ refers to banks limiting or withdrawing banking services from perceived ‘high-risk’ clients. ‘High risk’ is not merely commercial risk relating to a client’s ability to pay. It also includes ‘non-commercial’ risks such as client dealings in illicit funds or activities. Debanking decisions might also be made on operational-cost grounds where continued servicing of a particular customer base becomes uneconomical. In Australia, the de-banking issue has impacted migrant communities. More recently, de-banking has impeded the ability of digital assets service providers. Under the guise of rigorous compliance legal standards, Australian banks have limited or even cut-off banking services to many Australian digital asset firms. As the financial gatekeepers to the Australian economy, Australian banks (already very protected from competitors) are undermining an industry that could potentially compete for market share. Examining strategies adopted in other jurisdictions, Australian policy makers should supplement the introduction of a licensing regime, as proposed by the Digital Assets (Market Regulation) Bill 2023 (Cth), with additional balanced measures in order to support innovation in the digital asset sector and maintain financial integrity.

How do Ivorian Cyberfraudsters Manage Their Criminal Proceeds?

This 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.

Multi-class Bitcoin mixing service identification based on graph classification

Due to its anonymity and decentralization, Bitcoin has long been a haven for various illegal activities. Cyber-criminals generally legalize illicit funds by Bitcoin mixing services. Therefore, it is critical to investigate the mixing services in cryptocurrency anti-money laundering. Existing studies treat different mixing services as a class of suspicious Bitcoin entities. Furthermore, they are limited by relying on expert experience or needing to deal with large-scale networks. So far, multi-class mixing service identification has not been explored yet. It is challenging since mixing services share a similar procedure, presenting no sharp distinctions. However, mixing service identification facilitates the healthy development of Bitcoin, supports financial forensics for cryptocurrency regulation and legislation, and provides technical means for fine-grained blockchain supervision. This paper aims to achieve multi-class Bitcoin Mixing Service Identification with a Graph Classification (BMSI-GC) model. First, BMSI-GC constructs 2-hop ego networks (2-egonets) of mixing services based on their historical transactions. Second, it applies graph2vec, a graph classification model mainly used to calculate the similarity between graphs, to automatically extract address features from the constructed 2-egonets. Finally, it trains a multilayer perceptron classifier to perform classification based on the extracted features. BMSI-GC is flexible without handling the full-size network and handcrafting address features. Moreover, the differences in transaction patterns of mixing services reflected in the 2-egonets provide adequate information for identification. Our experimental study demonstrates that BMSI-GC performs excellently in multi-class Bitcoin mixing service identification, achieving an average identification F1-score of 95.08%.

Counter Measures to Combat Money Laundering in the New Digital Age

Money Laundering has been a significant concern for governments, law enforcement agencies, and financial institutions worldwide. With the advancement of technology, money laundering techniques have evolved in the digital age, presenting new challenges for authorities and financial institutions. Criminals leverage innovative digital platforms, cryptocurrencies, and virtual assets to launder illicit funds while maintaining anonymity and complexity in their transactions. In this article, we examine the money laundering techniques in the digital age and the challenges posed by these techniques and the implications for the global financial system. Furthermore, the article explores the role of regulatory frameworks, technological solutions, and international cooperation in mitigating the risks associated with digital money laundering. We also explore the countermeasures implemented to detect and prevent these illicit activities. Enhanced Know Your Customer (KYC) regulations, robust transaction monitoring systems, international collaboration, and innovative technologies are among the critical measures to combat digital money laundering.

Money laundering in global trade and the role of financial technology: The structured reviews

Money laundering in international trade facilitates the concealment of illicit funds through the manipulation of trade invoices and the exploitation of regulatory gaps. Addressing this issue involves improving traceability through financial technology, a promising solution. However, the adoption of such technology poses inherent risks and challenges that require careful consideration. This review synthesises knowledge on trade-related money laundering and financial technology, highlighting critical areas for additional research and improvement. Employing a Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) approach, academic databases, including Scopus and Web of Science (WoS), were systematically searched to identify relevant studies and articles. Advanced search techniques using keywords such as money laundering, trade-based money laundering, and financial technology resulted in the identification of 57 articles for eligibility. After excluding 20 articles due to being out of the field, having titles not significantly related, or abstracts not aligning with the study's objective, 37 eligible articles and conference proceedings were further examined. Two main themes were developed, concluding that the convergence of money laundering through digital trade and financial technology requires collaborative efforts among regulatory bodies, financial institutions, and technology experts. Such collaboration is essential to balance innovation and security, ensuring stability and prosperity in global economies.

Belt and Road Initiative: legal mechanisms to recover stolen assets

PurposeThis paper aims to determine the types of legal mechanisms that authorities can use to recover stolen assets for and from China.Design/methodology/approachNewspaper articles and books are examined as are relevant reports by various regulatory authorities and academic institutions.FindingsThe effectiveness of legal mechanisms in the recovery of stolen assets may be affected by issues such as the difficulties in tracing illicit funds, the ambiguous nature of “value” as well as the rise in technology.Research limitations/implicationsThere are limited data available in relation to the prevalence of corrupt officials along the Belt and Road Initiative and the statistical success in the recovery of stolen assets. Any discussions within this paper are based on the impressionistic observations of this author, which may not reflect the true state of affairs of the Belt and Road Initiative.Practical implicationsThose who are interested in examining how authorities could recover stolen assets from and for China will have an interest in this topic.Originality/valueThe value of the paper is to demonstrate the difficulties in recovering stolen assets for and from China.

The impact of demonetization on Indian economy

The demonetization strategy implemented by the Government of India on November 8th, 2016, was designed with the objective of eliminating illicit funds inside the economy and curbing the circulation of counterfeit currency, which were believed to be utilized for the purpose of financing acts of terrorism. Two further significant aims were to broaden the formal economy's scope and to make gradual progress in digital transactions. However, the implementation of this policy shock was deemed unjustified due to its potential to disrupt economic operations, particularly in the short term. The advantages and disadvantages of this approach have been subject to substantial deliberation and analysis within the realm of print media and policy discourse. However, it has been observed that there is a lack of empirical information about the influence of this policy shock on economic activity. Within the confines of this particular setting, employing econometric research, the current investigation has ascertained that demonetization did not provide a statistically significant influence on the general trajectory of economic growth. Instead, the repercussions were confined to certain sectors. Likewise, the effect of demonetization on inflation was particularly noticeable in relation to food costs only. However, a significant policy implication arising from demonetization is the transformative impact it has had on digital transactions in the years following its implementation.

An analysis of the determinants of money laundering in the United Arab Emirates (UAE)

PurposeIt is widely argued that money laundering (ML) is not a new phenomenon and the pervasiveness of ML is associated with some severe economic, social and political costs. Due to the lack of studies on the ML’s issue in the UAE, this study aims to examine the determinants of ML in the country between 1975 and 2020.Design/methodology/approachThe autoregressive distributed lag bounds testing results demonstrate the presence of long-run relationship between ML and the selected macroeconomics variables. The analysis is validated by the dynamic ordinary least squares, the fully modified ordinary least squares and the canonical co-integration regression estimators.FindingsThe estimation result reveals that while the real estate market, outflow of money, arms procurement and size of the underground economy influences the size of ML positively, gold trade, the level of financial development and the size of economic activities are negatively associated with ML, both in the short- and long-run.Originality/valueUp to date from a country-level analysis, no study has been devoted to the ML in UAE, except for Aljassmi et al. (2023). To the best of the authors’ knowledge, this study is the first to investigate the determinants of laundered money in the UAE economy. Based on these outcomes, strategies and measures which will deter the laundering of illicit funds through the real estate and gold market, remittance system, financial system and arms procurement contracts in the UAE are recommended.

Impact of informal remittance channels in Bangladesh: Understanding the role of hundi in financial crime beyond economic aspects

Despite the existence of legal and regulated systems, a significant proportion of Bangladeshi immigrants choose to utilize informal channels for the purpose of transferring funds. This practice has the potential to result in macroeconomic ramifications for Bangladesh. The rise of Hundi in Bangladesh has emerged as a noteworthy economic issue in recent times, particularly owing to its detrimental impact on the nation's foreign reserve and its utilization as a conduit for money launderers to unlawfully move funds abroad. The primary objective of this research is to analyze the implications of Hundi as a means of facilitating illicit financial operations. This study utilizes a qualitative research approach and a purposive sample consisting of 16 hundi dealers, 23 customers, and 7 senior bank officials working in the banking intelligence sector to investigate the hundi system's role in money laundering, despite the difficulties in accessing influential hundi dealers involved in significant transactions. The findings underscore the adverse economic consequences of Hundi, as it bypasses formal channels, thereby failing to contribute to Bangladesh's foreign reserves. Furthermore, it points out the exploitation of Hundi as a means for money laundering, enabling the assimilation of illicit funds into the legitimate economy, and supporting unlawful endeavors such as overseas property acquisition. The recommendations put forth suggest the implementation of strategies to enhance digital transactions, the establishment of a dedicated remittance application, and the design of a user-friendly agent banking system within the formal banking sector.

Food crime: An often-ignored money laundering typology and a predicate crime

Food crimes, including adulteration, poisoning, mislabelling, and misrepresentation of information, have cost billions in the global food industry. The coronavirus (COVID-19) pandemic has highlighted the weaknesses of the food supply chain. Unfortunately, such weaknesses are exploited by actors to engage in illicit activities. Consequently, this work aims to highlight the inherent susceptibility of the food sector to being exploited to launder illicit funds and as a predicate crime for generating illicit funds. This study emerges from two independent systematic literature reviews on trade-based money laundering and food crime to identify a knowledge gap highlighting the dual role of the food sector, both to launder illicit funds and as a predicate crime generating such funds. It adopts a viewpoint approach by considering the factors identified in the academic literature to outline the vulnerabilities of the food sector to illicit practices. The novelty of this study lies in focusing on the dual role of the food sector, which to date has been ignored.

Reporting Obligations for Attorneys in Money Laundering Cases: Attorney-Client Privilege Under Pressure?

AbstractWith the publication of the Panama Papers in 2016, law firms and attorneys came under the spotlight of international anti-money laundering efforts. It became clear that attorneys, protected by the attorney-client privilege, play a significant role in concealing the origin of illicit funds and the constructing of offshore company-schemes. The public outcry prompted legislators to hold these facilitators accountable and to prevent money-laundering activities by imposing reporting obligation on them, whenever there is the suspicion of a client being involved in illicit activities. Unsurprisingly, attorney and professional associations voiced considerable opposition to these legislative efforts claiming an erosion of the attorney client privilege and nothing less than an attack on the rule of law. This article examines the attorney-client privilege from a historical, empirical, and constitutional perspective. A brief analysis of the legal frameworks in Germany and Switzerland exemplifies how reporting obligations affect legal practice and what challenges exist for attorneys. Both countries are considered global hubs for money laundering activities. The legal concepts of holding attorneys accountable in the neighboring countries differ in some respects. In conclusion, it shows that the legal professions successfully managed to widely avoid a ‘responsibilization’.

The (un)usual suspects? Exploring the links between illicit financial flows, Russian money laundering and dependent financialization in the Baltic states

The paper analyses the links between illicit financial flows, money laundering and dependent financialization using the Baltic states as exploratory case studies. Since the restoration of their independence, Estonia, Latvia and Lithuania have been involved in several massive money laundering scandals, with illicit funds flowing mainly from Russia, as well as other former Soviet Republics. Currently, these episodes have taken on a new dimension in light of the Russian invasion of Ukraine. Until recently, the prevailing narrative was that illicit financial flows and money laundering in the Baltic states resulted from a failure in the financial system’s ability to monitor and detect these operations. However, this paper argues that far from being a simple shortcoming, money laundering and illicit financial flows in the Baltic states are products of dependent financialization in two main ways: first, in the decade leading up to the global financial crisis, the overall economic performance and the returns of financial actors in these countries became dependent on foreign capital inflows. This dependency was key to enabling the arrival of illicit financial flows and money laundering from the post-Soviet space, especially after the crisis. Second, due to its comparative advantages and its subordinate position in the international financial system, the banking sector of the Baltic states was used as an intermediary in global financial networks of money laundering for funds from the former USSR, where it assumed most of the financial, legal and reputational risks. Finally, the research also points to the emergence of new risks.

Estimating the magnitude of money laundering in the United Arab Emirates (UAE): evidence from the currency demand approach (CDA)

PurposeDespite the vulnerability of rapidly developing and emerging market economies, researchers have paid less attention to the determination of the size of money laundering (ML) in these economies, including the United Arab Emirates (the UAE). Therefore, this paper aims to estimate the magnitude of ML in the UAE between 1975 and 2020 based on the currency demand approach (CDA).Design/methodology/approachThe study uses the Gregory–Hansen cointegration technique alongside the autoregressive distributed lag bounds testing procedure to estimate the CDA model.FindingsThe results illustrate that an amount equivalent to about 19.034% of the GDP is laundered in the UAE between 1975 and 2020, on average, with the value lying between 15.129% and 23.121%. In addition, the results demonstrate the importance of the real estate market, gold trade, remittance channels and the size of the underground economy in facilitating the laundering of illicit funds in the country.Originality/valueTo the best of the authors’ knowledge, the study is the pioneering attempt at estimating the amount of illicit funds laundered in the UAE. Besides, the adoption of a novel, yet robust, approach based on the modification of the CDA technique also sets the study apart as it ensures a correct, clear, unambiguous and indisputable estimate of the magnitude of ML is obtained. In addition, it is expected that the outcome of the study will expand the frontiers of knowledge among policy makers and relevant agencies and ensure the adoption of the most efficient and effective measures to curb the ML menace in the country.

Factors influencing the choice of technique to launder funds: The APPT framework

This paper proposes a new framework to provide insights into the techniques launderers adopt to clean illicit funds, drawing on existing literature and theories including rational choice, public value, structural coupling, and stakeholder. The proposed APPT framework is named after four factors that explain the choice of techniques: the Actors involved, Predicate crime, the Purpose of laundering, and Technological innovations. While the current literature on money laundering primarily directs attention toward aspects such as regulatory frameworks, the stages of money laundering, and ways of detecting it, there is a lack of understanding about the reasons underlying a launderer’s choice of techniques. This paper endeavors to reduce this gap in the literature and contribute to understanding the motivation of money launderers for the benefit of investigations. The framework offers new insights for the money laundering literature and has implications for neophytes, practitioners, and institutions teaching financial crime.

Money Laundering: Factors Leading to Money Laundering in Gold Investment Company in Malaysia

Money laundering has always been one of the biggest frauds in the world and it has also been a serious issue in Malaysia. Money laundering can destabilize the economy of a country by introducing large amounts of illicit funds into the financial system, which can distort markets, increase inflation and undermine the integrity of financial institutions. This activity can be defined simply as a process of cleaning ‘dirty’ money to make it seem like the funds come from legitimate transactions. It is classified as a criminal activity since it uses a legal business to conceal the sources of their illegal incomes. Anti-Money Laundering, Anti-Terrorism Financing and Proceeds of Unlawful Activities Act 2001 (AMLA) was established to discuss the issue of money laundering in Malaysia. Some of the famous cases regarding money laundering are 1MDB, Shafee’s case and Genneva Malaysia Sdn. Bhd. This study focuses on the case of Genneva Malaysia Sdn. Bhd. that uses the gold bullion investment to cover up their money laundering activity. The stages in money laundering are placement, layering and integration. These three stages are usually being used by all criminals involved in this fraud activity. There are several factors leading to money laundering discussed in this paper which are pressure, opportunity, rationalisation and capability. This study is using literature review matrix method to understand influences of money laundering in Malaysia. This paper proposed some recommendations on how money laundering can be reduced especially in Malaysia.

Money Laundering: A Review

Money laundering is a major global issue, influencing the economy of pretty much every nation including India. This term has become a buzzword nowadays. Money laundering is an illegal process of concealing the origin of the money which is obtained from unlawful activities, but this is converted and is shown to be obtained from a legitimate source. Understanding the concept of money laundering and its nature is essential to combat it. There are different types and methods that money launderers use to disguise their illicit funds. This illegal activity has the simple purpose of converting black money to white money. This is done through activities like drug trafficking, corruption, or gambling. The real estate sector as a target, is the largest, most vulnerable, and easiest sector for money laundering. To deal with this worldwide issue, countries from everywhere implemented laws and regulations and are coming up with newer techniques.

A systematic literature review of money mule: its roles, recruitment and awareness

PurposeThis paper aims to provide a systematic literature review (SLR) on contemporary cardinal money mule issues.Design/methodology/approachThis paper reviews the most common money mule themes in perpetrating financial crime activities, especially its roles, recruitment and awareness. A systematic review protocol called preferred reporting items for systematic review and meta-analysis protocols is adopted for this study.FindingsMoney mules are used by organized criminal groups (OCG) or fraudster to launder illicit funds from outrageous criminal activities. They allow their accounts to be used for money laundering by OCG. The attacker, OCG or fraudsters would layer the stolen funds using money mule accounts. These money mules are recruited using various approaches, oftentimes deceived by opulent lifestyles to captivate the interest of potential money mules.Originality/valueThis paper presents money mule awareness needed by accountant, bank employees and the society. It is an unprecedented SLR on money mule. This paper will be beneficial for future money mule researchers, enforcement agencies and practitioners in banking industry.

Supranational detectives? Transnational market abuse and the politics of surveillance delegation in the EU

ABSTRACT National surveillance is often insufficient to identify transnational issues. One solution to this problem is to delegate to international organizations (IOs) the power to surveil activity in numerous states simultaneously, acting, in essence, as supranational detectives. When should we expect states to engage in such delegation? This article contends that this will depend on whether sub-state public agencies have acquired the exclusive capacity to surveil that phenomena at the national level. Those that have will actively oppose delegation to preserve the benefits afforded by that exclusivity, thereby reducing the likelihood that an IO is ultimately empowered to perform supranational surveillance. This hypothesis is tested against two case studies in which EU energy and securities regulators contemplated empowering an IO with supranational surveillance powers to detect transnational market abuse. Empirical evidence, drawing on 86 interviews, corroborates that each group’s pre-existing surveillance capabilities impacted their delegation preferences and, in turn, whether delegation occurred. These findings advance our understanding of supranational delegation and the politics of multi-level governance in the EU. Further, they shed empirical light on transnational market abuse, an understudied form of financial crime that hurts consumers, destabilizes prices, and facilitates the movement of illicit funds across borders.

Virtual money laundering: policy implications of the proliferation in the illicit use of cryptocurrency

PurposeThis study aims to explain how cryptocurrency is leveraged for illicit purposes across the global financial system. Specifically, it establishes how cryptocurrency has been changing the nature of transnational and domestic money laundering (ML). It then assesses the effectiveness of conventional anti-money laundering (AML) policy and legislation against the proliferation of crypto laundering, using Canada as a critical case study.Design/methodology/approachData was collected from court cases and secondary sources to build cross-case trends of cryptocurrency use in ML. Illicit International Political Economy forms the theoretical foundation for this study, whose contribution is situated in the current literature on crypto-ML.FindingsThis study finds that Bitcoin is common among crypto-money launderers, though most also use some form of alt-coin, and that the use of third-party currency exchanges is a prevalent method to create illicit funds and conceal proceeds of crime. The findings validate two hypotheses that illicit use of crypto is prevalent in the first two stages of ML, and that crypto is most often used in conjunction with other fiat currencies. Although law enforcement is improving on monitoring and understanding popular cryptocurrencies such as Bitcoin, alt-coins pose a significant challenge for criminal intelligence. New regulations for third-party currency exchanges are having a positive impact on curtailing crypto-laundering but are shown to be insufficient per se to contain the use of crypto in criminal activity.Originality/valueThis study contributes to a more robust understanding of the use of virtual currency in transnational and domestic ML. It contributes to an emerging body of literature on the role of technological change in enabling the global flow of illicit funds. It also informs public policy on virtual currency in general, and on AML regulation in Canada in particular.