Money Laundering Schemes Research Articles

A Holistic Network Analysis of the Money Laundering Threat Landscape: Assessing Criminal Typologies, Resilience and Implications for Disruption

Abstract Objective This article visualises money laundering, a crime spanning hundreds of different actors, methods and value instruments, as a network. Possible combinations of money laundering actions and schemes are analysed through a holistic visualisation to draw policy-relevant insights into their prevention. Methods A prior scoping review of money laundering typologies identified 793 activities that a money launderer can take to obfuscate illicit funds. These actions form the basis of a directed network graph showcasing all possible combinations of money laundering schemes. Three network-based analyses are then conducted: (1) centrality analysis, to determine the most ‘important’ money laundering actions as priorities for prevention, (2) resilience analysis to simulate iterative interventions against different money laundering actions to assess their impact on the wider network and (3) subgroup analysis to identify groups of commonly undertaken schemes (i.e. “typologies”). Results Money laundering is found to be a highly resilient process crime, with specific interventions often unable to prevent schemes from displacing to alternative activities to launder their funds. However, benefits of tactically displacing criminals to more easily detectable schemes are discussed. The formulation of money laundering typologies through more empirically robust processes is also motivated, in place of compartmentalised reports that remain the current standard practice. Conclusions Network analysis is motivated as an effective way of visualising complex process crimes with vast criminal opportunities such as money laundering, allowing policy-relevant insights to be drawn in terms of resource-allocation, strategy and prioritisation. Theoretical and policy implications of the current study are discussed in the context of crime scientific theories.

NEW AML TOOLS: ANALYZING ETHEREUM CRYPTOCURRENCY TRANSACTIONS USING A BAYESIAN CLASSIFIER

The emergence of cryptocurrencies as a form of digital payments has contributed to the emergence of numerous opportunities for the implementation of effective and efficient financial transactions, however, new fraud and money laundering schemes have emerged, as the anonymity and decentralization inherent in cryptocurrencies complicate the process of monitoring transactions and control by governments and law enforcement agencies. This study aims to develop a mechanism for analyzing transactions in the Ethereum cryptocurrency using a Bayesian classifier to identify potentially suspicious transactions that may be related to terrorist financing and money laundering. The Bayesian approach makes it possible to consider the probabilistic characteristics of transactions and their interrelationships to increase the accuracy of detecting anomalous and potentially illegal transactions. For the analysis, data on transactions of the Ethereum currency from June 2020 to December 2022 were taken. The developed mechanism involves determining a set of characteristics of transaction graph nodes that identify the potential for their use in illegal financial transactions and forming intervals of their permissible values. The article presents cryptocurrency transactions as an oriented graph, with the nodes being the entities conducting transactions and the arcs being the transactions between the nodes. In assessing the risks of using cryptocurrencies in money laundering, the number/amount of transactions to and from the respective node, the balance of these transactions (absolute value), and the type of node were considered. The analysis showed that among the 100 largest nodes in the network, 11 were identified as having a «critical» risk level, and the most closely connected nodes were identified. This methodology can be used not only to analyze the Ethereum cryptocurrency but also for other cryptocurrencies and similar networks.

The Impact of Cryptocurrency on Money Laundering Practices

The coming of cryptocurrencies has, amazingly, changed the face of the financial space. It has opened up opportunities and challenges in the field of money laundering. The deep impact of cryptocurrencies on the practice of money laundering becomes a detailed study. Since digital currencies are embedded with inherent characteristics, such as anonymity, decentralization, and the ease of performing cross-border transfers, criminals have now found new ways to conceal their illicit financial activities. The paper critically reviews how cryptocurrencies are used in money laundering schemes, evaluates the effectiveness of current legal provisions and anti-money laundering measures, and reviews case studies that exemplify real-world applications and challenges to regulatory bodies. Moreover, it offers recommendations on the use of new technologies, like blockchain analytics, toward better detection and prevention of money laundering through cryptocurrency. The paper thus provides a range of useful insights, associated with recommendations for the strengthening of the global regulatory framework in dealing with the increased threat of cryptocurrency money laundering, through a synthesis of the literature review, case analysis, and expert interviews. The paper contributes to this debate by providing insight into the challenges that regulatory authorities face and making recommendations to improve anti-money laundering efforts in the cryptocurrency space. This is done through an in-depth review of recent cases and legislation in this area. The findings were that, though cryptocurrencies pose a great challenge, innovative technology solutions coupled with international cooperation can play a vital role in mitigating the risks associated with cryptocurrency-based money laundering.

Potensi Kecurangan Non-Fungible Token: Dalam Lensa Akuntansi Forensik dan Syariah

This study analyzes the possibility of fraud in Non-Fungible Tokens (NFT) transactions using forensic accounting and Sharia perspectives. This study employs a qualitative research method with in-depth and exploratory approach. Primary data were collected through interviews with NFTs Creators, Auditors, and DSN-MUI Member, while the secondary data were from article journals, scientific books, theses, and websites. This study concludes that NFT has the potential for fraud, such as Pump-and-Dump, Rug Pull, and Money Laundering schemes, based on the nature of NFT itself. However, all of these fraud schemes can be prevented by the users (investors) who must be informed about what they are buying, either through educating themselves on fundamental analysis or by using forensic accounting techniques. From sharia perspective, NFT transactions are not permitted (haram) because they are lack of underlying assets and contain gharar (obscurity), dharar (danger), maysir (speculation), and also have been given a haram fatwa by the MUI of Indonesia.

A Case Study on Multi-Countries Money Laundering Scheme and A Proposed Automatic Detection System

This paper presents a case study on the Franco-Israeli syndicates orchestrating their cross-continental money laundering schemes. These money laundering schemes have been operating for over two decades, ever since China’s entry to the World Trade Organization in 2001. The paper reviews the operation of the money laundering schemes in detail and highlights the difficulties encountered by bankers and investigators in unearthing and investigating criminal activities within the banking systems. The paper then proposes an automatic anti-money laundering system, which is expected to address these difficulties. Preliminary experimental results show that the system successfully identifies the crux of these money laundering syndicates within a few days’ time, something which usually takes years of investigation to track down the suspects using traditional methods, as well as its ability to initiate pre-warning procedures to the banks and law enforcement agencies once suspicious transaction clusters are found. The paper concludes with a discussion on the legal implications encompassing the evidence projected by this system.

Cleaning mafia cash: An empirical analysis of the money laundering behaviour of 2800 Italian criminals

Despite the wide reach of anti-money laundering legislation worldwide and increasing media attention, fostered by journalistic leaks such as Panama Papers, empirical knowledge on how criminals launder their illicit proceeds is still scarce. The few available empirical studies show that money laundering (ML) schemes are often less sophisticated than they are depicted in the political and media debate. To contribute to the empirical knowledge of ML behaviour, and test this hypothesis, the present study analyses the ML activities related to 2818 Italian offenders included in the ML section of the LexisNexis’ WorldCompliance database. Through a quantitative content analysis of textual information related to each offender's profile, it highlights the characteristics of the ML offenders, the methods (or ‘typologies’ in FATF terms) employed, the assets seized, the business sectors involved and the countries in which ML was conducted. The results confirm that criminals tend to employ unsophisticated typologies, as well as prefer Italy or jurisdictions that are close (geographically and culturally) to Italy for laundering their illicit proceeds. Tangible assets (first real estate and registered vehicles) are more frequent than financial assets. Finally, differences exist between the laundering by mafia-related ML offenders and non-mafia ones. The study provides empirical ground to progress in the knowledge of how ML offenders behave, and supports the idea that criminals, when laundering their proceeds, do not act as legitimate entrepreneurs, but may be driven by other constraints and drivers.

Review of Regulatory Mechanism on Crypto Income

Some countries are actively considering taxing income from cryptocurrency exchanges. In addition to this, in many national and international policy decisions related to Cryptocurrency, regulators also focus on issues such as customer data, money laundering schemes and supporting terrorism. This article intends to examine the regulatory regime of cryptocurrency regulators—from a country-specific perspective.

Особливості протидії відмиванню грошей на сучасних фінансових ринках

The development of new financial technologies has led to a significant acceleration of cash flows, an expansion of the range of opportunities for settlements and the use of digital financial instruments. One of the negative consequences of this process was the emergence of new money laundering schemes. The aim of the article is to qualitatively assess the changes in the sphere of money laundering with the use of financial institutions caused by the development of new financial technologies and virtual instruments, as well as to determine the list of signs of transactions with virtual assets that may indicate the implementation of money laundering schemes. Virtual assets have significant potential to stimulate financial innovation and efficiency in financial markets, but their individual characteristics create new opportunities for money laundering and terrorism financing. In view of this, it is of great importance in modern financial markets to improve methods of counteracting this phenomenon, in particular, the formation of a list of signs of transactions with virtual assets, which may indicate the illegal origin of funds or illegal purposes of their movement. The publication proposes an approximate list of signs of money laundering, which can be used by financial service providers in the process of monitoring transactions. Our approach involves dividing such attributes into six categories according to the volume and frequency of transactions, transaction patterns, anonymity, characteristics of transaction beneficiaries, source of funds, and geographic risk. A list of signs of suspicious activity when carrying out transactions, the use of assets with a high level of anonymity, client risks, links with criminal activity or high-risk jurisdictions has been determined. In order to understand the big picture and qualitatively assess the risks of money laundering and terrorism financing, the features identified in the article should be considered in the context of all available information on individual transactions. Taking into account the features and vulnerabilities of the latest financial instruments, we consider it an important prerequisite for updating the current practices of customer due diligence and detection of suspicious financial transactions.

Financial content of money laundering concept: literature review

The article presents the review of scientific publications on combating money laundering (AML). The subject of the study is economic phenomena and processes that reveal the role of financial sector in AML. The purpose of the article is to provide scientific arguments for and against the encumbrance of financial organizations with anti-money laundering measures, to identify the research gaps in publications and to focus on their solution. Methodology and approach: database of e-library, ResearchGate, Academia conducted a systematic review of publications on AML with an emphasis on the specific features of various financial and non-financial institutions. The study identifies their main topics, such as the main resource of shadow economy, money laundering schemes, ML landscape, the role of banks in ML. The author provides an in-depth analysis of the publications indicated in the links of the selected articles as well as the gaps in research that should be studied in future. The paper reveals a promising direction of research, due to the lack of scientific publications on the problem of administering adequate punishment from regulatory authorities to individuals and banks for non-compliance with anti-money laundering norms, allowing to maintain a balance between the severity of punishment (in order to prevent future violations) and maintaining the stability of business processes in banks (in order to strengthen banking system reputation).

Assessment of Anti-Money Laundering Practices on Financial Crime Prevention Among Commercial Banks in Kenya

Commercial banks are instrumental to socio-economic development of any Country. In Kenya, the banking sector contributes approximately 5% of Gross Domestic Product. These institutions provide among others; reliable payment system and access to credit to individuals, corporate and government(s). However, they are a target for many economic crimes including money laundering schemes. This study examined the anti-money laundering practices and financial crime prevention among commercial bank in Kenya. The study adopted a descriptive research design. The sampling frame and unit of analysis was the 39 commercial banks in Kenya (CBK, 2023). The unit of response was 117 managers of these 39 commercial banks. Primary data was collected using a close-ended questionnaire for the predictand and the response variable. In order to assess the internal consistency of the instrument, a pre- test was carried out using managers of three Micro Finance Banks in Nairobi, Kenya. Multiple linear regression was used for inferential analysis after testing the data for Gaussian distribution, linearity and autocorrelation and multicollinearity. The study found that 33.1% of the variations in financial crime prevention could be explained by anti-money laundering practices and that they had a statistically significance influence of financial crime prevention. The study recommended that commercial banks review the anti-layering practices and anti-integration practices as they do not appear to support financial crime prevention. These among others will provide a mechanism of enhancing financial crime prevention among commercial bank and hence reduce exposure arising from anti-money laundering practices trends currently experienced in the banking sector in Kenya.

Economic and Legal Principles of Cybersecurity as a Prerequisite for the Introduction of Special Economic Regimes

The article conducts a scientific and practical study of the economic and legal aspects of the State policy in the field of cybercrime and its impact on business development in a particular region, country, etc. It is determined that the massive spread of cybercrime, the lack of effective mechanisms for combating economic crimes, and the leveling of conceptual approaches to creating an effective mechanism for legal support of the business environment development have a negative impact on the investment environment in particular and on ensuring sustainable development of the State as a whole. The author analyzes the regulatory and legal documents which form the legal basis of the mechanism for combating cybercrime, both at the international and national levels. The author identifies the weaknesses of the national system of legal regulation of cybersecurity. The author points out the sufficiency and fragmented nature of legislative support for cybersecurity and counteraction to the growth of economic crimes.
 It is established that the significant vulnerability of Ukraine's information sphere is due to the excessive use of foreign-made material and technical means. It is emphasized that the international scale of the fight against cybercrime requires clarification and harmonization of national legislation in order to be able to cooperate with law enforcement agencies abroad. The article focuses on the low efficiency of Ukraine's current cybersecurity system and the urgent need to improve and optimize it. Achieving this will not only solve the problem of information space security, but also ensure the continuity and sustainability of Ukraine's economic development.
 It is determined that one of the priority areas of work in the field of creating optimal conditions for business is the fight against computer crimes in the economic sphere. Among the main tasks in this area of activity is to counteract the legalization of shadow income. The analysis of money laundering schemes shows that organized crime is very interested in using the capabilities of electronic payment systems which allow for instant money transfers with almost complete anonymity of counterparties.

Combating modern methods of legalisation (laundering) of the funds obtained by criminal means with the use of cryptocurrency

The problems of combating corruption have not lost their relevance over the years. Tolerant attitudes to corruption as a way to quickly solve everyday problems give rise to new ways of developing illegal activities in various spheres of public life. At the same time, while fully condemning corruption as a means of illicit enrichment, the majority of the population still follows the old path. Consequently, the interests of individuals aimed at enriching themselves by any means, including illegal means, are becoming a counterweight to the development of society.
 Money laundering remains a significant problem in the area of combating corruption. Unfortunately, the methods and means of carrying out illegal activities in order to conceal them and avoid responsibility for their commission are being updated on a daily basis. Successful money laundering requires high intelligence and an understanding of the processes of working with modern financial technologies. One of the areas of money laundering is the use of various types of cryptocurrencies and NFTs. The funds held by the offender go through a complex route before reaching their final destination. Illegally obtained funds introduced into the legal financial system in such a way as to avoid unnecessary questions about the origin of the money, through a significant number of transactions, are integrated into the financial system and can be used for any purpose.
 The current state of research on the development of cryptocurrencies as a tool for money laundering is not sufficiently disclosed at the national level. Most of the scientific works are of foreign origin. The article is aimed at finding ways to improve the current anti-corruption legislation. The author outlines the main features of the development of money laundering schemes using cryptocurrency as an instrument of such schemes. The author defines the main definitional categories of such concepts as “cryptocurrency”, “NFT”, “smurfs”, “drops”, etc. The main shortcomings of the institutional and regulatory mechanism for detecting and investigating this category of offences have been highlighted, taking into account the use of modern financial technologies. The study may be useful in improving legislation in the field of corruption prevention.

Parallel path detection for fraudulent accounts in banks based on graph analysis.

This article presents a novel parallel path detection algorithm for identifying suspicious fraudulent accounts in large-scale banking transaction graphs. The proposed algorithm is based on a three-step approach that involves constructing a directed graph, shrinking strongly connected components, and using a parallel depth-first search algorithm to mark potentially fraudulent accounts. The algorithm is designed to fully exploit CPU resources and handle large-scale graphs with exponential growth. The performance of the algorithm is evaluated on various datasets and compared with serial time baselines. The results demonstrate that our approach achieves high performance and scalability on multi-core processors, making it a promising solution for detecting suspicious accounts and preventing money laundering schemes in the banking industry. Overall, our work contributes to the ongoing efforts to combat financial fraud and promote financial stability in the banking sector.

Audit, Fraud, and Forensic Accounting

First, the paper will define fraud and analyze a fraudulent accounting situation and the responsibilities of a forensic accountant. Then, the paper will examine and analyze an accounting fraud case involving a money laundering scheme involving a retired couple who own a business and their son. Lastly, the paper will offer insight into the differences between an accounting audit and a fraud examination of financial statements and recommendations on what current fraud model offers the best explanation for the actions of the fraudulent retired couple.

The new money laundering machine through cryptocurrency: Current and future public governance challenges

The purpose of this paper is to examine the role of cryptocurrency in facilitating money laundering and identify different methods and services that send funds through numerous addresses or businesses to obscure their origins using cryptocurrency. The methodology for conducting this research is qualitative. A literature review that involves a systematic and rigorous approach to identifying, analyzing, and synthesizing existing research on the use of cryptocurrency as a money laundering instrument has been taken into consideration. We identified in the first selection more than 150 research papers published between 2002 and 2021. Our results show that cryptocurrency is used in money laundering schemes, including the purchase of cryptocurrencies by criminal networks using illicit proceeds and the use of cryptocurrencies to transfer funds. The biggest issue facing virtual currency currently is that the same attributes that attract legitimate users, such as anonymity, as well as speed and global reach, also attract criminals. Money laundering has had devastating social implications for societies. Our research helps to focus attention on the problems of using cryptocurrency in money laundering practices and possible interventions by the authorities in the form of regulation

Combatting money laundering in Saudi Arabia

PurposeThe purpose of this paper is to examine the effectiveness of the antimoney laundering measures in the Kingdom of Saudi Arabia in response to its commitments to the Financial Action Task Force and treaties in combatting money laundering.Design/methodology/approachTo explore the effectiveness of the Saudi antimoney laundering measures, this research’s data have been obtained by a qualitative approach that uses a combination of primary and secondary resources. It relies on analyzing Anti-Money Laundering Law (AML) and the process of money laundering detection in Saudi Arabia in relation to three cases from Saudi courts supported by journal articles, academic books and reliable websites.FindingsThis study concludes that the Saudi AML has been efficient and effective in the battle against money laundering. This study finds that there is close coordination and collaboration between financial institutions, banks and governmental agencies in Saudi Arabia to combat this phenomenon. This study also concludes that the AML is compatible with other criminal laws such as the Anti-Bribery Law, the Anti Trafficking in Person Law and the Anti-Drug Trafficking Law.Research limitations/implicationsThis paper relies mainly on publicly available information regarding the detection of money laundering schemes and the confiscation of proceeds of crime in the Kingdom of Saudi Arabia as a main source of information. There data available on the money laundering cases in the Saudi prosecution and criminal courts were limited due to the lack of public disclosure of such cases because of their sensitivity. This was made up for by using reliable sources in which some cases were reported.Originality/valueThis paper underlines the efficient aspects of the current AML that contribute to reduction of money laundering in Saudi Arabia. This paper emphasizes on the importance of the structure of collaboration between regulatory, financial and law officers to implement the rule of law and achieve justice.

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.

The evolution of trade-based money laundering schemes: a regulatory dialectic perspective

PurposeThe purpose of this study is to apply the regulatory dialectic to describe the evolution of trade-based money laundering (TBML) schemes, to describe three recent TBML innovations uncovered by a large bank in the important global trade jurisdiction of the United Arab Emirates (UAE), and to provide recommendations for an effective regulatory response.Design/methodology/approachThe methodology used is a caselet approach with three examples of TBML schemes recently foiled in the UAE as well as an application of the regulatory dialectic literature to TBML.FindingsThe implications of the regulatory dialectic for research regarding TBML and associated regulation and compliance will enable regulators, the financial services sector and academics to understand TBML and the ever-evolving steps criminals are taking to circumvent the changing landscape of regulation and controls implemented by the financial services sector and customs tasked with mitigating such behaviour. This paper will bring awareness of the evolution of TBML, the controls and frameworks that may be used to prevent, detect and investigate some of the complex schemes of TBML.Research limitations/implicationsThe regulatory dialectic theory provides insights into the evolution of TBML schemes as well as why compliance activities tend to be reactive, rather than proactive. The cases covered in this paper provide insights into the nature of this circular process between financial crime and regulation, which is useful for anti-financial crime professionals and regulators focusing on deterrence.Practical implicationsThe UAE is a small, rapidly developing trade and finance center in the Middle East, surrounded by nations that are sanctioned, in active conflicts, politically unstable and/or highly corrupt. TBLM undermines the security of the UAE; the authors provide insights into criminal innovations and regulatory responses.Social implicationsTo promote the safety and stability of the ten million residents of the UAE, and others in the Middle East and North Africa (MENA) region, it is important to understand the process of innovation in TBML schemes and regulatory response.Originality/valueTo the best of the authors’ knowledge, this paper is the first to apply the regulatory dialectic theory to TBML to describe innovation in TBML schemes and to provide cases describing contemporary TBML innovations in the MENA region.

Incorporating machine learning and a risk-based strategy in an anti-money laundering multiagent system

Over the last decade, the international community has become more aware of the danger and harm caused by the practice of the crime of Money Laundering (ML). Organizations to combat this crime were created and the existing laws were expanded and tightened. Complex legislation, combined with the increase in the volume of financial transactions involved in money laundering schemes, motivated research targeting the improvement and automation of the critical processes of detecting, signaling and communicating suspicious clients. The Anti-Money Laundering (AML) activity is strongly impacted and dependent on this process, which has evolved slowly, in part due to its subjectivity and complexity. This article presents the characteristics of a multiagent system that incorporates machine learning and risk components to identify and flag suspicious bank clients. It also seeks to help human specialists in the analysis of suspicious behavior by these clients. The knowledge bases are obtained through data mining over a real database, obtaining for each client a transactional behavior pattern, enriched with specific rules based on legal aspects, and on the expertise of the AML analysts of the financial institution that funds this research. The adopted risk strategy seeks to identify and classify the ML risk level of each flagged client. To evaluate its results, the system analyzed six months of actual transactions. A set of candidate clients was produced and subsequently investigated by the financial institution’s AML analysts, who proved a high degree of correctness in the indicated suspicions, including cases that were not flagged by the antecedent systems in execution for decades at the institution.

ЕФЕКТИВНІСТЬ СИСТЕМИ ФІНАНСОВОГО МОНІТОРИНГУ В УМОВАХ БЕЗГОТІВКОВОГО СУСПІЛЬСТВА

This article attempts to evaluate the effectiveness of the financial monitoring system in the conditions of a cashless society. It is shown that the use of cash to carry out illegal transactions is only one of many tools that allow persons involved in the process of laundering dirty money to escape the control of the financial monitoring system. As a result, focusing on fighting only with this tool will lead not so much to increasing the efficiency of the financial monitoring system, but to the reorientation of persons, engaged in laundering dirty money, to use other mechanisms of bypassing the financial monitoring system. It was determined that the main factors that simplify the development of new tools and mechanisms for getting out of the control of the financial monitoring system and reduce the effectiveness of the formal rules of financial monitoring are: inconsistency of the purpose of payment with the actual sold goods or services provided; the use of a generally accepted substitute for the official monetary unit; opportunities to use illegal/shadow income to buy goods on the shadow market. It is shown that in the case of application of the discrepancy between payment assignment and actual sold goods, the effectiveness of getting out of the control of the financial monitoring system will depend on the correctness of the choice of the accompanying goods. In the case of the use of a generally accepted substitute for the official monetary unit, the effectiveness of getting out of the control of the financial monitoring system will depend on the prevalence of this substitute. It has been proven that the main flaw of the financial monitoring system, which ultimately determines its low level of efficiency, is its inflexibility, not its inability to effectively counteract new, previously unknown, money laundering schemes. As a result, each fundamentally new money laundering scheme will remain operational and invisible to the financial monitoring system until the main mechanisms of its operation are revealed and changes are made to the formal rules of financial monitoring that will make its use impossible.