Role of money mules in money laundering and financial crimes a discussion through case studies

Raza, Muhammad Subtain; Qi, Zhan; Rubab, Sana

doi:10.1108/jfc-02-2020-0028

Cited by 20 publications

(25 citation statements)

References 8 publications

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“…Although a key aspect of assessing the effectiveness of SARs is the accuracy and completeness of the reports financial institutions submit, other factors, such as the ability of financial institutions to identify suspicious transactions and the use of information from these reports by law enforcement agencies, must also be considered when assessing the effectiveness of SARs (dalla Pellegrina et al 2020;Raza, Zhan, and Rubab 2020;Khan et al 2022;Chen et al 2018).…”

Section: Related Workmentioning

confidence: 99%

“…The findings from Figure 3 provide a clear understanding of the tactics criminal networks use to launder money across borders. Fund transfers are the preferred method, followed by checks and physical currency exchanges (Raza, Zhan, and Rubab 2020). Because of the increased level of scrutiny that accompanies these types of transactions, government payments and gaming instruments are often the last option launderers consider to move illicit funds across international borders.…”

Section: Industrymentioning

confidence: 99%

“…or debit cards specifically (Raza, Zhan, and Rubab 2020;Singh and Best 2019). As such, organizations are advised to be extremely vigilant when it comes to investigating any suspicious behavior linked to these two areas to prevent fraud from occurring.…”

Section: Financial Instrumentsmentioning

confidence: 99%

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Predicting Suspicious Money Laundering Transactions using Machine Learning Algorithms

Lokanan

Maddhesia

2023

Preprint

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This study employs machine learning techniques to identify key drivers of suspicious activity reporting. The data for this study comes from all suspicious activities reported to the California government in 2018. In total, there were 45,000 records of data that represent various features. The paper uses linear regression along with Lasso, Ridge, and Elastic Net to perform feature regularization and address overfitting with the data. Other probabilistic and non-linear algorithms, namely, support vector machines, random forests, XGBoost, and CatBoost, were used to deal with the complexity of the data. The results from the mean squared and root mean squared errors indicate that the ensemble tree-based algorithm performed better than the statistical and probabilistic models. The findings revealed that filings from regulators, the type of products, and customers' relationships with the institutions were the top contributors to SAR filings. Through the evaluation of a vast amount of data, this study provides valuable insights for identifying suspicious activities in financial transactions and has the potential to significantly improve suspicious transaction monitoring.

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Section: Related Workmentioning

confidence: 99%

Section: Industrymentioning

confidence: 99%

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Predicting Suspicious Money Laundering Transactions using Machine Learning Algorithms

Lokanan

Maddhesia

2023

Preprint

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“…Federation may be presented as follows (Feofilova et al, 2020;Frunza, 2015;Ionina, 2019;Kopytina, 2020;Nizovtsev et al, 2021;Raza et al, 2020;Sukhoterin et al, 2017;Zali & Maulidi, 2018;Zhubrin & Lavronenko, 2018):…”

Section: The Classification and Typology Of Transactions Related To M...mentioning

confidence: 99%

The Financial Aspect Of Money Laundering Operations

Dendiberya¹

2022

The European Proceedings of Social and Behavioural Sciences

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This article reports on the issue of financial transactions related to the legalization (laundering) of income criminally obtained. It focuses on the nature and structure of such financial transactions, taking into account national peculiarities. The review of the basic peculiarities of the mentioned interactions has been carried out in terms of quantitative indices, the opinions on the reliability of their values, and also the reasons for their decrease have been given in the paper. The analysis of classification and the specific scheme of the specified operations in the Russian Federation were carried out. The basic models (by the number of phases) used for operation performing on legalization (laundering) of incomes received by a criminal way were defined. The characteristic of phases with the account of the application of the concept of management of the movement of incoming and outgoing financial (money) flows was made. The research analyzes significant problems in organizing the system of counter illicit financial flows. The analysis of regional peculiarities of money laundering operations, based on the peculiarities of organization of economic relations, peculiarities of financial operations inside the territory of subjects, the economic activity of population and financial organizations registered in the Khabarovsk region was carried out.

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“…There are a number of articles that address the issue of suspicious money laundering transactions from a theoretical perspective (Levi et al 2018;He 2010;Simser 2013), as well as articles that address the same issue through case studies (Naheem 2016;Raza et al 2020;Gilmour 2020), but an approach from the statistical perspective of the suspicious transactions available in the annual reports for recent years has not been found.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficiency of Money Laundering Countermeasures: Case Studies from European Union Member States

Cotoc

Nițu

Şcheau

et al. 2021

Risks

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The aim of this study is to present the trends and effectiveness of money laundering countermeasures from the perspective of a number of suspicious transactions reported to the Financial Intelligence Units (FIUs), a number of analysis results submitted to law enforcement authorities, and the typologies of cases in European Union Member States. In order to determine the impact of the joint effort in the fight against money laundering, we used descriptive statistics to process the data and case studies from annual reports of the European FIUs for 2018 and 2019. The results of our study highlight the increase in the number of suspicious transactions notices, as well as in their quality level. There is an increasing tendency towards information exchange between European Union countries regarding the suspicion of money laundering, but there is no stable trend for referring cases to law enforcement and other responsible institutions. Based on the available data, it can be concluded that the EU anti money laundering measures are efficient, but further steps are needed to achieve higher international coordination and cooperation.

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Role of money mules in money laundering and financial crimes a discussion through case studies

Cited by 20 publications

References 8 publications

Predicting Suspicious Money Laundering Transactions using Machine Learning Algorithms

Predicting Suspicious Money Laundering Transactions using Machine Learning Algorithms

The Financial Aspect Of Money Laundering Operations

Efficiency of Money Laundering Countermeasures: Case Studies from European Union Member States

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