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Transaction laundering has become an increasingly intricate and rampant form of financial misconduct in the age of digital commerce. This research paper conducts an exhaustive examination of this issue, categorizing the various techniques criminals use to highlight areas where existing risk management practices could be further refined. Amid escalating regulatory scrutiny of both financial and nonfinancial entities, the paper stresses the implications of not meeting regulatory standards. As a novel contribution, this study advocates for a shift in risk management strategies. It argues that entities under obligation should harness advanced technological methods to counter transaction laundering challenges effectively. The study serves as a relevant guide for online businesses aiming to strengthen their measures against transaction laundering. For future work, the potential effectiveness of technology-driven countermeasures deserves further scrutiny.

This study used a conceptual legal research method, using a library-based doctrinal legal research approach with a conceptual legal perspective, drawing from existing literature. This study reviewed primary and secondary legal sources, including case law and provisions of the Money Laundering (Prohibition) (Amended) Act, 2012, and the Terrorism (Prevention) Act 2013 (as amended). This study also assessed the provisions of the Economic and Financial Crimes Commission (Establishment) Act, Laws of the Federal Republic of Nigeria, 2004. This research further incorporated a blend of archival and secondary legal sources. This study conducted comparative analyses, examining the legal frameworks of Canada, the UK, Hong Kong and China alongside Nigeria to identify potential lessons for enhancing Nigeria’s legislation concerning money laundering and terrorism financing. This study also assessed problems and derived insights from the study’s findings. This research method was chosen to establish the credibility of the findings regarding the issues of money laundering and terrorist financing.

The analysis uses a comprehensive network dataset, encompassing ties among individuals and businesses in the Netherlands from 2005 to 2019. It integrates administrative data, including family ties, shared bank accounts and employment history, with corporate information and ownership relations from the Chamber of Commerce. Criminal data related to police interventions, legal convictions and suspicious money laundering transactions are linked to these networks. This unique approach overcomes the scarcity of large empirical datasets in criminological research, offering valuable insights into criminal network behavior and dynamics. Understanding how criminal networks adapt to anti-money laundering policies aids regulatory authorities in designing more effective and efficient measures while also enhancing the tools available to enforcement authorities for detection and investigation.

AML policies are often criticized for their high costs relative to the perceived benefits. This paper's method avoids dark number estimations and relies on high-quality administrative data. The theoretical contribution includes an examination of specialization, competition and collaboration within criminal networks. The empirical aspect uses a unique dataset and emerges as a methodology for evaluating the effects of AML policy measures using temporal cluster analysis.

The purpose of this study is to examine the impact of anti-money laundering (AML) regulations on accrual earnings management (AEM) and real earnings management (REM) in Iran’s emerging capital market.

The panel data regression is used to testing hypotheses. The sample includes 2,020 data and 202 companies listed on the Tehran Stock Exchange (TSE) over a period of ten years from 2012 to 2021. Also, the companies covered in this study include financial and nonfinancial companies. Furthermore, the data related to the research variables were extracted from the annual financial statements and the TSE database.

The results show that compliance with AML regulations leads to a reduction in AEM and REM. In other words, companies with higher money laundering (ML) tend to manage their earnings, which is in line with agency theory.

This study has implication for policymakers and regulators, auditors and managers. Considering the negative impact of AML regulations on earnings management (EM), Iranian auditing firms need to emphasize on the full implementation of AML regulations in TSE. Also, the results of this research may aid policymakers and regulators to detect financial crimes through accounting signals.

To the best of the authors’ knowledge, this is the first study in an Iran capital market to examine the impact of AML regulations on EM in financial and nonfinancial companies. Previous research has not controlled for the effects of financial companies. Prior studies have not examined the effects of financial companies. In addition, this study differentiates itself from previous studies by introducing a new method for measuring the independent ML variable based on auditor opinions. The obtained data can aid international bodies to better understand compliance with ML regulations in Iran and can reduce their concerns in negotiations.

Regarding the magnitude of the impact caused by money laundering, the size of the organization and the many parties involved, this paper aims to explore the methods used in detecting money laundering, especially the use of technology.

This research is a literature review from various research sources originating from Pro-Quest, Emerald, Science Direct and Google Scholar.

The researchers found that the most widely used methods for detecting money laundering were artificial intelligence, machine learning, data mining and social network analysis.

This research is expected to help the government or institutions such as the police, forensic accountants and investigative auditors in the fight against money laundering. This research is limited to only a few sources, and it is hoped that further research can explore more deeply related to other methods for detecting money laundering.

This paper discusses the methods that are widely used in detecting money laundering.

This study aims to focus on the legal status of the Financial Action Task Force (FATF) regulatory spread in spite of its limited membership in international law. This is conducted by examining the regime of the FATF with the normative regime of public international law and trying to identify common grounds and conflicts between the two.

This study adopted an exploratory approach involving a thorough examination and analysis of accredited text, command papers and reports, archival materials, national obligations, websites as well as other documentary evidence.

This research gives an empirical determinant of compliance behaviour in response to FATF regulatory standards and the interplay of international law.

The findings here are not exhaustive and could be approached from other perspectives. Researchers are therefore encouraged to engage by testing the findings further, as this is only a blueprint for further research.

This study provides implications for the need to open up the current membership of the FATF, as it appears discriminatory in nature and could inhibit effective compliance with its regulatory standards.

FATF regulatory standards do not just revolve around its members and rule-takers but also affect unintended and vulnerable people who were never in contemplation when these regulations were debated without a global consensus.

The main aim of this study is to advocate for a rethink of FATF’s regulatory strategy by ensuring that its operations are more inclusive, where jurisdictions can participate as members, creating a sense of belonging and commitment in the fight against money laundering.

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.

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.

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.

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.

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.

The purpose of this paper is to examine the extent to which the corporate social responsibility (CSR) law will help combat money laundering in the United Arab Emirates (UAE).

The paper will first focus on examining whether money laundering and CSR are compatible. Such an analysis will then inform decisions on whether to include anti-money laundering in CSR disclosure requirements.

Key findings from the analysis have shown that the UAE CSR law does not explicitly mention money laundering as part of CSR disclosure requirements. Anti-money laundering (AML) and CSR are compatible and convergence, but money laundering is not yet an integral element of CSR disclosure requirements.

There are no clear mechanisms or provisions under the UAE CSR law on how money laundering can be included in CSR disclosure requirements, whether voluntary or mandatory. A pressing challenge now is whether the UAE should regulate AML/combatting the financing of terrorism disclosures under the CSR law. The main concern is that such a move could make mandatory disclosure another technical and regulatory requirement that UAE business must comply, which will be inimical to fostering a strong CSR culture.

This paper aims to provide authorities managing free trade zones, business enterprises, financial institutions and dedicated free zone customs, police and immigration command assigned to deal with aspects of movement of goods and persons in and out of the free zones with a clear understanding of the cross-border financial crime risks associated with the African Continental Free Trade Area and the risk control measures that combines human intelligence with advanced technology to combat cross-border financial crimes in the African Continental Free Trade Area.

A range of research activities would be used in this study. In addition to a sweeping literature review of academic, official studies and media writings, the main focus is on critically evaluating and analysing primary data by searching and collecting statutes, court cases, administrative rules and regulations and policy documents.

This paper identified bribery and corruption; modern slavery; and trade-based money laundering as the financial crime risks that are of priority concern to African Continental Free Trade Areas and demonstrated how countries can assess and mitigate these risks through adequate policies, procedures and controls including appropriate compliance management arrangement and adequate screening procedures to ensure high standards when hiring employees; corporate transparency; training on managing incidents of modern slavery, forced labour and third-party exploitation; and appropriate monitoring framework for trade-based money laundering activities.

While many authors have written research papers on intra-African trade, none of those research papers explained how countries can assess and mitigate financial crime risks in free trade zones. This research paper describes the ways in which cross-border financial crime risks can be assessed and adequately addressed by the authorities managing free trade zones. This research paper analyses the risk assessment topic in line with the African Continental Free Trade Area with a focus on free trade zones in Nigeria. This research paper would help authorities managing free trade zones, commercial organisations and business enterprises to identify, prevent and mitigate cross-border financial crime risks. Zone managements and business enterprises that implement the risk-based approach, in line with the guidance given in this research paper, will be well-placed to avoid the consequences of inappropriate de-risking behaviour.

This study aims to investigate the impact of FinTech on money laundering within the context of Nigeria. The motivation stems from observations suggesting that FinTech platforms might be used for illicit money transfers, particularly from developed to developing economies. While existing literature predominantly highlights the positive aspects of FinTech, there's a dearth of studies addressing its potential association with money laundering. Current understanding of this relationship relies heavily on anecdotal evidence derived from reported or convicted cases. Thus, the primary goal of this study is to analyze the influence of FinTech on money laundering while also considering the moderating effects of financial regulation and financial literacy as perceived by users. The research delves into regulatory perspectives concerning money laundering and FinTech.

To fulfill the study's objectives, a quantitative research design is used. A survey of 248 FinTech users in Nigeria is conducted using structured questionnaires. Data collected from the questionnaires is analyzed using partial least square structural equation modeling (PLS-SEM).

The quantitative analysis revealed a significant relationship between FinTech and money laundering and that financial regulation moderates the relationship between FinTech and money laundering in Nigeria, but such was not established with respect to financial literacy. The results of the quantitative approach that uses secondary data are consistent with the qualitative approach. FinTech the results indicate the presence of technology induced money laundering in Nigeria. Regulating technology-based anti-money laundering poses serious challenges for developing countries due to the absence of specific laws that mitigate the threats.

The paper focuses on Nigeria as a case study, which may limit the generalizability of the findings to other countries with different FinTech ecosystems, regulatory frameworks and financial literacy levels.

The finding is useful in developing guidelines and regulations by policymakers and strategies by practitioners in relation to FinTech, money laundering, financial regulation and financial literacy. On the basis of the above, the authors recommend regulation at the national and industry level to mitigate the adverse effect of technology on money laundering. Thus, multilateral partnerships can help in tackling tech-induced money laundering through strengthened cooperation.

Money laundering risks: The study highlights that FinTech, while beneficial, also poses significant risks for money laundering activities, especially in developing countries like Nigeria. Regulatory Importance: It emphasizes the critical role of financial regulations in mitigating the risks associated with FinTech and money laundering. Financial Literacy: The paper suggests that financial literacy does not significantly moderate the relationship between FinTech and money laundering, indicating the need for stronger regulatory measures rather than relying solely on financial literacy. Policy Formulation: The findings are crucial for policymakers to formulate strategies that balance the benefits of FinTech with the need to prevent money laundering and ensure financial system integrity.

This research presents a novel approach to methodology, specifically focusing on the qualitative research design, addressing population, sampling techniques and data collection methods. It emphasizes techniques aimed at ensuring measurement quality and achieving research objectives. Data collection used survey questionnaires, while analysis involved both statistical package for social science (SPSS) and PLS-SEM. SPSS facilitated descriptive and preliminary analyses, while PLS-SEM confirmed measurement quality and tested hypotheses. Ethical considerations were paramount throughout the research process, underscoring the commitment to maintaining originality in research endeavors.

The purpose of this paper is to examine the influence that the occurrence of greenwashing has on the consumer perception of corporate social responsibility (CSR).

This paper observed the market indication that a consistent undermining of authentic commitment to CSR taints consumer perception. Investigating how the motivations behind greenwashing contribute to the presentation of CSR was the first means of examining the market forces. Consumer orientation was used as a guiding principle to consider the short- and long-term perspective of a greenwasher.

Individual instances of greenwashing contribute to a collective deterioration of marketplace trust in the promises of CSR. The negative influence on CSR is not isolated to the greenwashing perpetrator but casts a wider effect. The consequences of greenwashing are not isolated but widely dispersed.

Whilst much of the literature focuses on the stigmatisation of individual firms, it is crucial to note how marketplace trust is eroded. In addition, the perception of CSR-related regulations is for example influenced but rarely recognised as a consequence of greenwashing behaviour.

This paper aims to elucidate the practical and theoretical mechanisms which contribute to the perception of an economic sanction’s effectiveness as a foreign policy tool.

This paper is divided into three sections, the first two of which are heavily based on the current academic literature and media presentation of sanctions. The third section is rooted in the empirical approach presented in the first author’s exploratory work, Methods of Money Laundering (2021).

Economic sanctions cannot be perceived as effective when the standard for efficacy remains undefined and sanction circumvention remains feasible. The public perception of sanctions is characterized by a series of assumptions as well as conflict foreign policy objectives, which cultivate an economic theory that is benefited by a practical exploration of the routes of circumvention.

The efficacy of economic sanctions is not a stable equation, but rather the application of an economic tool which is dependent on its context. Paths of sanction circumvention remain open due to weaknesses in compliance regulation. These paths continue to undermine the credibility of sanctions and, ultimately, their efficacy.