Journal of Money Laundering Control最新文献

Purpose

Drug trafficking in the tiny state of Manipur, located in the northeastern part of India bordering Myanmar, has drawn attention from all over the globe looking at the scale and varieties of drugs trafficked, ranging from plant-based opiates to synthetic-based amphetamine-type stimulants (ATS). Moreover, drug trafficking in the region also comes with many socio-political dynamics such as high per-capita drug consumption, local drug manufacturing units, terror funding from drug money, politician–drug lord nexus, police–peddler nexus.

Design/methodology/approach

The study is based on data from the years 2007 to 2023 accessed from the Narcotics and Affairs of Borders, a specialized branch of Manipur Police, Government of Manipur. The study also tries to estimate the state’s drug economy using the Financial Action Task Force and the United Nations Office on Drugs and Crime methodology.

Findings

The study finds seizure of a massive cache of heroin/brown sugar, and ATS in the past 4–5 years. The study also finds large-scale destruction of poppy plants in the state. The study also finds a high percentage of ethnic minority communities involved in drug trafficking. The study found the value amounting to US$62m in 2022. The study also comes across low conviction rates of drug traffickers in the state.

Originality/value

The study emphasizes the need for expediting the War on Drugs campaign in the state curtailing poppy cultivation and conviction of drug lords so that the nerve center of terror funding in India’s eastern front is kept under control.

Purpose

This study aims to conceptualize the UAE’s whistleblowing model by reviewing recent legislative updates directed toward removing potential legal deterrents, introducing legal protection and establishing numerous external whistleblowing channels. The study surveys these initiatives through the prism of the country’s unique socio-economic and judicial environments.

Design/methodology/approach

The study applies a conceptual approach to probe the potential impact of the UAE’s legislative initiatives on the country’s whistleblowing regime by connecting the demographic data, the UAE’s legal and regulatory frameworks, academic literature and media reports.

Findings

Recent legislative updates to the UAE whistleblowing regime are geared toward removal of potential legal deterrents, introduction of legal protection and establishment of external whistleblowing channels for reporting. These constitute the conceptual model of the UAE’s whistleblowing strategy, which is broad in scope and application yet may appear fragmented.

Originality/value

The study merges a comprehensive review of legislative initiatives and regulatory framework with academic literature to conceptualize the UAE’s whistleblowing model.

Purpose

This study aims to describe and empirically explore a new method for bank anti-money laundering (AML) systems using machine learning models. Current automated money laundering detection systems are notorious for flagging many false positives, causing bank employees to spend unnecessary time manually checking transactions that do not constitute money laundering. Decreasing the number of false positives can free up resources for investigating money laundering.

Design/methodology/approach

This study uses unique bank data on small- and medium-sized enterprises (SMEs) to examine how various client risk classification models can predict future suspicious transactions. This study explores various sources of client risk data and machine-learning approaches.

Findings

Client risk classification models can accurately predict suspicious future transactions. Adding accounting data and credit score information to client risk classification dramatically improves accuracy. This makes it easier to balance the risk of missing suspicious transactions with the need to reduce the number of false positives.

Practical implications

The suggested approach with readily available data sources and a focus on classifying client risk in a dynamic model can help banks significantly improve their efficiency by targeting their AML efforts toward the riskiest clients.

Originality/value

To the best of the authors’ knowledge, this study is the first to empirically explore machine learning in client risk classification, document how machine learning in client risk classification can significantly reduce false positives by incorporating novel, but readily available sources, such as credit risk and accounting data.

Purpose

This study aims to explore the relationships between GDP growth, education spending, central bank transparency (CBT) and accountability on the corruption perception index within the G20 countries, emphasizing their combined effects and interdependencies.

Design/methodology/approach

Using the central bank transparency index (CBTI) introduced by Dinçer et al. (2019), an analysis spanning from 2002 to 2019 was conducted on selected G20 countries, further refining the results by excluding EU members. Data sources included World Bank statistics and CBTI data. The research deployed the heteroskedastic and contemporaneously correlated panel-corrected standard error model to detail the effects of the aforementioned factors on the corruption index.

Findings

The study revealed no statistical evidence that economic growth had an effect on reducing corruption. Education spending emerged as a potent tool in curbing corruption, especially in EU nations. A strong correlation was identified between CBT and reduced corruption, consistent across G20 countries, regardless of EU affiliation. The insights emphasize the importance of enhancing education spending and CBT in combating corruption. For effective anti-corruption measures, countries are encouraged to invest more in education, amplify internal checks and adopt transparent central bank policies. Further research could delve into cultural, historical and political variables to understand corruption dynamics comprehensively.

Originality/value

This study aspires to address the existing gaps in the literature and provide a substantial contribution to the ongoing discourse and efforts to understand and mitigate corruption within the G20 countries and globally.

Purpose

The new technology-enabled means to transfer funds or value via crypto assets have prompted regulators and supervisors to question the effectiveness of the anti-money laundering (AML) regulatory framework. This paper aims to examine the recent developments of the EU AML legislation – leading up to the 2021 AML package – focusing in particular on the banks’ internal governance obligations.

Design/methodology/approach

The analysis is based on the legal dogmatic methodology and is therefore conducted thanks to a critical exam of the current and upcoming EU policy and legislation, taking into account the relevant literature and case-law.

Findings

The recent regulatory developments, culminating in the AML regulation, are strengthening the causal links between ML risk assessment–ML risk exposure–ML risk management, via internal governance procedures. One of the major AML regulatory strategies to react to the new challenges brought up by crypto assets amounts to a stricter and more demanding AML risk management regime imposed on banks.

Originality/value

The originality of this article lies in the analysis of the causal connection between money laundering risk identification and internal governance obligations. In particular, this article examines how the risk assessment will be shaping the organizational procedures, processes and internal functions necessary to manage the money laundering risks.

Purpose

This paper aims to propose a new research agenda that integrates the often-overlooked insights and experiences of compliance professionals into anti-money laundering (AML) policy formulation and academic research. It seeks to highlight the importance of a bottom-up approach in developing AML strategies that are not only theoretically robust but also practically effective and grounded in real-world application.

Design/methodology/approach

Using a comprehensive literature review and theoretical analysis, this study outlines six broad research focus areas. These areas are explored through the lens of existing theoretical frameworks that underscore the significance of practical insights, interdisciplinary collaboration and adaptive policymaking in enhancing AML efforts.

Findings

This paper highlights a significant gap in current AML research and policymaking, namely, the underrepresentation of compliance professionals’ perspectives. It argues that integrating these frontline insights can lead to more nuanced and effective approach to AML.

Practical implications

Adopting the proposed research agenda could significantly enhance the practical applicability of AML policies, leading to more effective prevention and detection of financial crimes. It encourages the development of support systems for compliance professionals, fostering a workforce that is both competent and resilient.

Social implications

By promoting a more inclusive and practice-based approach to AML policymaking, this paper advocates for a societal shift in how money laundering is tackled.

Originality/value

This paper contributes to the AML discourse by proposing a shift towards a more inclusive research and policymaking paradigm that values the contributions of compliance professionals. It extends the existing literature by suggesting a comprehensive framework for bridging these divides, thereby offering a novel perspective on enhancing the effectiveness of AML strategies.

Purpose

The purpose of this article is to review the legislation on limitation on cash payment from a comparative perspective with France. This legal provision has been the subject of inconsistency and lack of clarity for the past two decades.

Design/methodology/approach

This paper uses a doctrinal legal research technique based on an analysis of the law and how it is interpreted in relation to Mauritius's prohibition on cash payments. Section 5 of the FIAMLA 2002 is interpreted in large part by this assessment using legal precedents from the Supreme Court and other Mauritius judicial authorities. France has been chosen as the comparative jurisdiction as it has well-defined legal framework on cash payment limitations in Europe.

Findings

The Mauritian judiciary has played a far more significant and active role than the French judiciary. A cursory search reveals a dearth of case law concerning the interpretation of the pertinent sections of the French Monetary and Financial Code concerning the prohibition on cash payments. The French legal system places more emphasis on the kinds of transactions that are exempt, whereas the Mauritius system places more attention on the entities that are exempt, such as banks and other financial organisations.

Originality/value

This paper fills in the gap that exists on legal interpretation of legislation on limitation on payment by cash in Mauritius. It originally contributes to legal literature on money laundering by undertaking a comparison between Mauritius and France for the benefits of students and researchers around the world.

Purpose

This study aims to investigate the role of freight forwarding companies in detecting and reporting trade-based money laundering. The proximity of freight forwarding companies to shipping-related trade-based money laundering red flags places them in an ideal position to detect suspicious transactions.

Design/methodology/approach

The study used semi-structured interviews with expert participants in freight forwarding shipping and compliance aspects around freight forwarding. This study focuses on the South African context.

Findings

Freight forwarding companies are well-positioned to detect, investigate and report on trade-based money laundering schemes. However, the companies are not always aware of the guidelines designed to assist in identifying trade-based money laundering schemes. Thus, freight forwarding companies develop internal processes to identify trade anomalies but are often unable to link trade anomalies to illegal financial flows and trade-based money laundering schemes.

Research limitations/implications

The current regulations on money laundering can be extended to freight forwarding companies by the respective regulators for enhanced anti-money laundering protection. This study is limited to freight forwarding companies in a South African context.

Practical implications

Increased awareness among staff in freight forwarding companies can assist them in identifying trade-based money laundering red flags to detect and prevent trade-based money laundering schemes.

Social implications

This paper assists other role players and policymakers in the trade process to create a better awareness of trade-based money laundering. The limited obligations on freight forwarding companies to comply with anti-money laundering regulations lead to a more volunteer-like compliance practice.

Originality/value

To the best of the authors’ knowledge, this is the first paper that offers insight into the role of freight forwarding companies in detecting trade-based money laundering in South Africa.

Purpose

The purpose of this paper is to study the turnover of Italian shell companies (SCs)/missing traders used for tax crimes, a predicate offence of money laundering. This research could be useful for Italian obliged entities to the Anti-Money Laundering Law to detect and report SCs, as soon as possible, to the Financial Intelligence Unit for Italy.

Design/methodology/approach

The author uses a sample of 32 SCs that are present in the Third Penal Section of the Italian Supreme Court in the period 2018–2020, involved in tax crimes and that have presented their balance sheets for two or more years. For SCs, the author computes the averages for: the turnover growth rate from first and the maximum turnover; the years between these two values; and the years in which SCs are active. Moreover, the author verifies if SCs are similar in terms of turnover by studying the relationship between the turnover growth rate and the first turnover and the reduction of turnover standard deviations.

Findings

SCs growth is very high and they reach, on average, their peak in less than three years; SCs are active, on average, for about four years; eventually, SCs exhibit a convergence process in turnover levels.

Originality/value

To the best of the author’s knowledge, there are no studies that analyse the SC turnover.

Purpose

This paper aims to examine the association between money laundering (ML)/terrorist financing (TF) risks (hereafter, money laundering risks) and democratic governance across 117 countries.

Design/methodology/approach

A cross-sectional design was used to examine the association between ML risks and democratic governance by a quantitative approach. The findings are based on annual ratings of 117 countries on ML/TF risks and democracy while controlling for criminality and peace. The data was compiled from the Basel Anti-Money Laundering/Countering Financing Terrorism Risks Index, the Economic Intelligence Unit (Democracy Index), the Global Initiative against Transnational Organized Crimes (Criminality Index) and the Institute for Economics and Peace Index for 2020.

Findings

A multiple linear regression model found a statistically significant negative association between democratic governance and ML risks (B = −0.354, t = −7.454, p = <0.001) and a significant positive association between criminality and ML risks (B = 0.242, t = 2.692, p = 0.008).

Research limitations/implications

A cross-sectional design cannot determine causal inferences and generalization (Levin, 2006). The study only used a year to examine the hypothesis of a negative correlation between ML risks and democratic governance, thus making generalization difficult.

Originality/value

Extant literature examined ML, terrorism and AML diversely. There was a need to estimate the association between ML risks and democratic governance, especially globally, during a global crisis like COVID-19, when democratic principles, such as the rule of law, transparency and accountability, are challenged. Many personnel were laid off, thus limiting supervision for ML and TF. This study presents evidence of this association.