Laundering Methods Research Articles

Inovasi PRO GALO untuk Meningkatkan Kompetensi dan Pembelajaran Pemeliharaan Pakaian Pelindung

This research aims to enhance the maintenance practices of Aircraft Rescue and Fire Fighting (ARFF) protective clothing through the implementation of the Proficient Rinse and Optimal Garment Laundering (PRO GALO) system, which integrates advanced washing and rinsing techniques. Utilizing a Research and Development (R&D) approach, this study systematically developed a prototype based on the analysis, design, development, implementation, and evaluation model. The findings reveal that the PRO GALO system significantly improves garment cleanliness, odor removal, and durability compared to traditional laundering methods. Quantitative assessments demonstrated superior performance in preserving fabric integrity, colorfastness, and seam strength. Feedback from ARFF personnel and cadets indicated high satisfaction rates, highlighting the system's user-friendliness and time-saving advantages. Expert validation further emphasized the innovative aspects of the system, enhancing safety and operational readiness in emergency response situations. The implications for ARFF operations and the Aviation Fire and Rescue Study Program stress the importance of integrating advanced cleaning technologies to prepare future professionals better. Ultimately, the PRO GALO system represents a significant advancement in ensuring reliable protective gear for ARFF personnel.

The Use of Artificial Intelligence to Detect Suspicious Transactions in the Anti-Money Laundering System

Artificial intelligence (AI) is being actively implemented in anti-money laundering (AML) systems due to its potential to improve the detection of suspicious transactions. The article examines AI's effectiveness in detecting and reducing financial crimes of private military companies. The research employs machine learning (ML) algorithms and neural networks, anomaly detection methods, and economic impact assessment. A combination of supervised and unsupervised learning methods enables the creation of accurate predictive models for detecting money laundering anomalies. The results show that AI models outperform traditional rule-based systems, reducing false positives by 30% and increasing high-risk detection by 25%. This proves the advantages of AI over conventional anti-money laundering methods, which often cannot adapt quickly. The research emphasizes the transformative impact of AI on anti-money laundering systems, optimizing accuracy and resource allocation. Further research should focus on improving AI algorithms and their application in new financial technologies.

Enhancing anti-money laundering capabilities: The strategic use of AI and cloud technologies in financial crime prevention

Integrating Artificial Intelligence (AI) and Cloud Technologies is transforming the fight against money laundering in the financial sector. As digital financial platforms become more prevalent, traditional Anti-Money Laundering (AML) methods are proving inadequate against increasingly sophisticated criminal tactics. This study examines how AI and Cloud Technologies can enhance AML capabilities by improving real-time threat detection, reducing false positives, and ensuring compliance with global regulatory standards. Through a qualitative analysis of recent literature and case studies, the research highlights the effectiveness of AI in identifying complex, suspicious activity patterns that traditional systems often miss. Cloud Technologies complement AI by offering scalable, flexible, and secure solutions, enabling financial institutions to manage evolving risks and regulatory demands better. The findings suggest that the strategic use of these technologies represents a significant advancement in financial crime prevention. However, the study also notes challenges, including concerns about data privacy and the need for specialized skills to manage AI systems. The conclusion emphasizes that while AI and Cloud Technologies provide powerful tools for enhancing AML frameworks, ongoing research, and development are needed to address these challenges and fully realize their potential in safeguarding the financial system. This strategic adoption of technology marks a critical shift in combating financial crimes, ensuring that financial institutions remain resilient against the dynamic threats from money laundering.

The Varieties of Money Laundering and the Determinants of Offender Choices

Two images dominate discussion of money laundering. Investigative journalists and politicians stress the variety and sophistication of methods that have been used to launder money of corrupt officials and white collar offenders. The research literature, largely dependent on criminal cases, emphasizes how unsophisticated and routine are the laundering methods used by drug dealers and other illegal market participants. The discrepancy may reflect the incapacity of police to detect sophisticated money laundering but it may also represent the reality; different groups of offenders choose different methods. This paper presents a theoretical framework to explain how offenders choose to launder their criminal earnings. Specifically it asks: what determines the sophistication of the method chosen? Among the variables that we suggest influence the choice are: (a) the type of predicate crime and of crime proceeds, (b) the type of offender (age, education, social status), (c) his/her motivations, (d) the AML environment and the level of AML controls. The paper provides arguments from criminological and economic theory for how these variables might play a role. Without claiming that individual cases can test the theory, we offer some case narratives to suggest the plausibility of the factors that we propose.

Motivating a standardised approach to financial intelligence: a typological scoping review of money laundering methods and trends

AbstractObjectivesA comprehensive scoping review, followed by visual analyses of results, was conducted to understand the overall money laundering threat landscape.MethodsA PRSIMA-ScR-compliant review of 105 money laundering ‘typologies and trends’ reports was conducted, coding different components of money laundering and addressing the often-inconsistent nature of typologies reporting.ResultsThe review identified 16 typologies, over 200 value instruments, over 200 actors/entities and 2565 red-flag indicators relevant to money laundering. Results were visualised to identify aggregate trends, including the suspicious activities with which these actors/entities and value instruments are typically involved.ConclusionThe review suggests that a more holistic and cross-typological approach to reporting money laundering-related financial intelligence can assist in fostering better data sharing and cooperation across jurisdictions. Implications are drawn for how ‘typologies’ can be reported and articulated across relevant stakeholders in a more standardised and effective manner to improve prevention measures.

Kripto Para Merkezli Kara Para Aklama Senaryolarının Adli Bilişim Açısından İncelenmesi

One of the biggest innovations brought by the digitalized world is undoubtedly the invention of crypto money, which is decentralized, anonymous and complex, and connected to blockchain technology. This relatively new technology has attracted the attention of many people with its revolutionary changes in payment systems and great price movements in the market, as well as the economic balances it has changed around the world. In addition to this interest, it also attracted the attention of crime and crime organizations in a short time, and over time it turned into a tool used by illegal organizations such as laundering the proceeds of crime. Although this structure was initially exposed to the reaction of some states at the level of nation states, on the other hand, it managed to get the support of many states. However, although the spread of blockchain-based money laundering methods is an undeniable problem for all states, a significant cooperation has not been achieved by international collaborations and organizations to prevent this situation. On the other hand, it is of great importance for law enforcement and forensic analysts to clarify this situation and to fight against these structures in order to protect national interests. In this study; In this study, an approach that will detect money laundering is tried to be presented through sample scenarios by bringing a broad perspective to crypto money-based money laundering methods, which are very difficult to trace due to their nature. In addition, it is expected that the difficulties in implementation of the proposed approach will be clearly addressed and will shed light and inspire further study.

A synthetic data set to benchmark anti-money laundering methods

Bank transactions are highly confidential. As a result, there are no real public data sets that can be used to investigate and compare anti-money laundering (AML) methods in banks. This severely limits research on important AML problems such as efficiency, effectiveness, class imbalance, concept drift, and interpretability. To address the issue, we present SynthAML: a synthetic data set to benchmark statistical and machine learning methods for AML. The data set builds on real data from Spar Nord, a systemically important Danish bank, and contains 20,000 AML alerts and over 16 million transactions. Experimental results indicate that performance on SynthAML can be transferred to the real world. As use cases, we present and discuss open problems in the AML literature.

Anti-money laundering supervision by intelligent algorithm

As global anti-money laundering (AML) protocols and technologies strengthen, traditional laundering methods increasingly face stringent scrutiny. Concurrently, the allure of virtual currencies for laundering illegal funds is magnified, owing to their immunity from seizure, elusive traceability, and seamless cross-border transactions. This necessitates the design of specialized AML strategies for virtual currencies to counter this burgeoning avenue of illicit money circulation. Our study introduces a groundbreaking two-tier algorithm, marrying heuristic rules and integrated learning modalities, designed to enable risk-based detection of virtual currency money laundering. By employing data science methodologies, we scrutinize the distribution of statistical risk attributes within existing transaction samples to institute heuristic rules. By training an amalgamated model of Long Short-Term Memory (LSTM) and Graph Convolutional Neural Network (GCN), we can effectively discern conspicuous anomalous money laundering patterns across diverse transaction datasets. The integrated learning segment deploys a hard voting mechanism, bolstering the recognition of laundering techniques by synergizing multiple anomaly detection classifiers such as Histogram-Based Outlier Scoring (HBOS) and Isolation Forest. This methodology facilitates the detection of laundering activities in unlabeled data, generating explicit anomalous transaction data and concurrently capturing implicit abnormal transactions undetected by heuristic rules. Our approach alleviates the difficulty of procuring labeled money laundering data for AML identification, simultaneously improving the generalization and accuracy of unsupervised learning methods for money laundering detection.

Money laundering as a negative economic factor in the European Unio

Aim: Among the money laundering methods, virtual methods stood out, which can be considered more dynamic and less traceable than traditional money laundering methods. One of the great challenges of our time is money laundering in the developing cyberspace. Due to the dynamic development of money laundering methods and their importance in cyberspace, their influence on the national economy is also significant. The primary goal of the study is to explore the European Union and Hungarian legislative background of anti-money laundering, as well as its effectiveness in defense.Methodology: The Authors carried out a systematic review of the relevant international and Hungarian literature related to money laundering. After the literature review, as the main tool of protection against money laundering, the legal regulation was examined. Regulatory deficiencies have been identified that may form the basis of future legal regulations.Findings: As a result of the research, it can be summarized that the legislation in force in the European Union and Hungary is not ready to regulate Internet money laundering methods, regulations and legislation are always one step behind money laundering committed by virtual methods. In order to effectively defend against money laundering, changing the legal background and developing monitoring activities are considered particularly important tasks.Value: In Hungary and the territory of the European Union, the criminal law tools prove to be few in the fight against money laundering, especially against crimes committed on the Internet. The regulations and some proposals of the European Union and Hungary do not provide a solution to the majority of potential risks and loopholes arising from virtual currencies. Therefore, it is necessary to clarify the exact legal status of virtual currencies. The study highlights the shortcomings of the current legal situation, and this initiative draws attention to the current situation of certain virtual currency service providers receiving an operating license, which also requires compliance with anti-money laundering rules, so that e-money and various payment services are also stricter they could come under control. The Authors review the process of money laundering, provide an international perspective on the most frequently used money laundering methods, and explain the importance of virtual money laundering and possible defense methods.

Optimal home and hospital laundering of reusable surgical scrubs: Systematic literature review.

Theatre personnel can spread healthcare-associated infections through contaminated surgical scrubs. Decontamination of surgical scrubs through optimal methods is important to minimise transmission of microorganisms from theatre personnel's clothing to different areas in the hospital and their homes. This study aimed to review the literature on the optimal home and hospital laundering methods for the decontamination of reusable surgical scrubs worn by theatre personnel. A systematic literature review of previous studies on laundering reusable surgical scrubs was performed. A review question was formulated using the patient, intervention, comparison and outcome (PICO) framework. A literature search was performed using ScienceDirect, Web of Science, ProQuest, EBSCOhost and Google Scholar. A direct link could be established between the cycle length and water temperature. The higher the water temperature, the shorter the washing cycle required. After a load has been washed in low or medium water temperatures, tumble drying and ironing should follow. Despite the water temperature, a disinfectant must be added to the load. Health professionals and hospital management should be aware of optimal laundering guidelines for hospital and home laundering as part of infection control. Water temperature, time, mechanical action, type of disinfectant and heat are factors influencing the successful removal of bacteria and other pathogens and represent the baseline of this article. Home-laundering of reusable surgical scrubs should follow strict guidelines. When these specific guidelines are applied, the effects of home-laundered scrubs will not negatively impact either the theatre or the home environment.

CYBERCRIME MONEY LAUNDERING CASES AND DIGITAL EVIDENCE

The widespread dependence on digital systems and increased value of digital commerce in the metaverse boosted cyber vulnerability. The cybercrime will be more profitable than the global trade of all major illegal drugs combined, while Cybersecurity Ventures expects global cybercrime costs to grow by 15 percent annually by 2025. Cybercrime changed traditional money laundering methods which is difficult to detect since it could be committed from anywhere in the world. The threat posed by cybercrime money laundering methodologies has been aggravated by the Covid-19 pandemic.
 To investigate cyber laundering the e-evidence are crucial, which is confirmed by the EU Commission estimate that 85 percent of criminal investigations require electronic evidence. Additional challenge for law enforcement authorities presents the fact that the organised cybercrime is joining forces and their likelihood of detection and prosecution is estimated to be 0.05 percent in the USA. Furthermore, the digital evidence is often held by service providers as private companies based in another country, which causes many obstacles to access to those data by investigative and law enforcement authorities. 
 The paper identifies impact of Covid-19 on cybercrime and increased risks of cyber laundering. In relation to investigation and prosecution of cyber money laundering, the paper analyzes challenges for investigative authorities to gather data and evidence in cyber money laundering cases and efforts of EU and USA authorities to facilitate access to digital evidence and relevant data stored by service providers. The paper refers to possible shortcomings of proposed instruments and need for efficient response and adaptation to changes in the cybercrime.

Use of Preliminary Exposure Reduction Practices or Laundering to Mitigate Polycyclic Aromatic Hydrocarbon Contamination on Firefighter Personal Protective Equipment Ensembles.

Chronic health risks associated with firefighting continue to be documented and studied, however, the complexity of occupational exposures and the relationship between occupational exposure and contaminated personal protective equipment (PPE) remains unknown. Recent work has revealed that common PPE cleaning practices, which are becoming increasingly more common in the fire service, are not effective in removing certain contaminants, such as polycyclic aromatic hydrocarbons (PAHs), from PPE. To better understand the relationship between contaminated firefighter PPE and potential exposure to PAHs, and to gain further understanding of the efficacy of cleaning practices, we used a standardized fire exposure simulator that created repeatable conditions and measured PPE surface contamination levels via wipe sampling and filters attached to firefighter gear worn by standing mannequins. This study examined the effects of repeated (40 cycles) PPE cleaning (laundering and on-scene preliminary exposure reduction (PER) techniques) and repeated exposures on PAH concentration on different surfaces. Further exploration included examination of contamination breakthrough of turnout jackets (comparing outer shell and interior liner) and evaluation of off-gassing PAHs from used gear after different cleaning treatments. When compared by jacket closure type (zipper and hook and dee), total PAH concentration wiped from gear after exposure and cleanings showed no significant differences. Regression analysis indicated that there was no effect of repeated exposures on PAH contamination levels (all sampling sites combined; before fire 10, 20, and 40; after fire 1, 10, 20, and 40; p-value > 0.05). Both laundering and on-scene PER significantly reduced contamination levels on the exterior pants and helmets and were effective at reducing PAH contamination. The jacket outer shell had significantly higher PAH contamination than the jacket liner. Both laundering and wet soap PER methods (post-fire) are effective in reducing surface contamination and appear to prevent accumulation of contamination after repeated exposures. Semi-volatile PAHs deep within the fibers of bulky PPE are not effectively reduced via PER or machine laundering, therefore, permitting continued off-gassing of these compounds. Further research is needed to identify the most effective laundering methods for firefighter turnout gear that considers the broad spectrum of common contaminants.

On Some Historical Aspects of Money Laundering in Russia and China

Aim. In this article, the author seeks to analyze some of the characteristic features of various forms of money laundering in Russia and China, with reference to the chronicles of past centuries, starting from the moment this phenomenon arose, which later became widespread in both countries.Tasks. To realize the main aim, the author gradually solves logically interconnected tasks: firstly, to identify the oldest forms of legalization of illegal income in Russia and China; second, to trace the logic of evolutionary changes in money laundering in the historical practices of both countries; thirdly, compare the Russian and Chinese experience in the studied system of economic structural and functional ties.Methods. When writing the material, methods of chronological reconstruction, historical analogy, analysis and synthesis, comparative studies were used.Results. The author established that for the first time corruption mechanisms for the legalization of illegal income arose in China in the 4th century BC, while in Russia this practice is clearly traced only from the 15th century. The article shows that in China during the Tang Dynasty (VII–X century AD), money laundering methods demonstrated active development, and then reached a level critical for maintaining statehood in the era of the Opium Wars (XIX century), although they were subsequently partially leveled during the socialist period of Chinese statehood in the twentieth century. By analogy, the author considers the historical background of the evolution of money laundering mechanisms in our country in the era of feudal fragmentation, as well as tsarist and Soviet power. The article attempts to compare two historical paintings — Russia and China.Conclusion. The author concludes that the processes of legalizing illegal funds in Russia and China have similar features and are intensified in connection with the most important historical events, therefore, modern models of money laundering and countering this illegal activity have characteristic features formed by cultural experience in a particular country.

Effect of Household Laundering, Heat Drying, and Freezing on the Survival of Dermatophyte Conidia.

Dermatomycoses are one of the most common dermatological infectious diseases. Dermatophytoses, such as tinea pedis (athlete’s foot) in adults and tinea capitis in children, are the most prevalent fungal diseases caused by dermatophytes. The transmission of anthropophilic dermatophytoses occurs almost exclusively through indirect contact with patient-contaminated belongings or environments and, subsequently, facilitates the spread of the infection to others. Hygienic measures were demonstrated to have an important role in removing or reducing the fungal burden. Herein, we evaluated the effectiveness of physical-based methods of laundering, heat drying, and freezing in the elimination of Trichophyton tonsurans, T. rubrum, and T. interdigitale conidia in diverse temperatures and time spectra. Based on our findings, laundering at 60 °C was effective for removing the dermatophyte conidia from contaminated linens. On the contrary, heat drying using domestic or laundromat machines; freezing at −20 °C for 24 h, 48 h, or one week; and direct heat exposure at 60 °C for 10, 30, or 90 min were unable to kill the dermatophytes. These results can be helpful for clinicians, staff of children’s communities, and hygiene practitioners for implementing control management strategies against dermatophytoses caused by mentioned dermatophyte species.

The comparative analysis of regulations in the Italian Republic and the Russian Federation against cryptolaundering techniques

PurposeIn the age of DarkNetMarkets proliferation, combatting money laundering has become even more complicated. Constantly evolving technologies add a new layer of difficulty to already intricated schemes of hiding the cryptocurrency’s origin. Considering the latest development of cryptocurrency- and blockchain-related use cases, this study aims to scrutinize Italian and Russian antimoney laundering regulations to understand their preparedness for a new era of laundering possibilities.Design/methodology/approachOne of the most recommended ways to buy and sell cryptocurrencies for illegal drug trade on DarkNet was discovered using machine learning, i.e. natural language processing and topic modeling. This study compares how current Italian and Russian laws address this technique.FindingsDespite differences in cryptocurrency regulation, both the Italian Republic and the Russian Federation fall behind on preventing cryptolaundering.Originality/valueThe main contributions of this paper: consideration of noncustodial wallet projects and nonfungible token platforms through the lens of money laundering opportunities, comparison of Italian and Russian antimoney laundering regulations related to cryptocurrency, empirical analysis of the preferred method of trading/exchanging cryptocurrency for DarkNet illegal trade using machine learning techniques and the assessment of how Italian and Russian regulations address these money laundering methods.

Behind the criminal economy: using UK tax fraud investigations to understand money laundering myths and models

To launder money is, by definition, to obfuscate and to hide, which makes it a notoriously difficult topic to study. Data access is another challenge contributing to the underdeveloped base. This paper presents an in-depth exploratory analysis of previously untapped data from the UK’s tax enforcement agency. We examine a sample of money laundering investigations (n = 31) over a three-year period, together involving 52 suspects. Against these cases, we test the applicability of the most widely used international model of money laundering: the three-stage model of placement, layering and integration (FATF, 2019). We also examine who was responsible for the offences and which laundering methods they used. A focus group with professionals helped us explore possible interpretations and implications of our findings. Overall, the results undermine the utility and validity of the ubiquitous three-stage model: it applied in under a third of cases. Cash couriers featured heavily and thus merit further attention, as do the cost-benefit decisions behind choosing between different money laundering methods. This study has relevance for academics, law enforcement, policy-makers and industry professionals alike.

Money laundering through cryptocurrencies - analysis of the phenomenon and appropriate prevention measures

PurposeThe aim of this paper is to assess the relevance of cryptocurrencies with regard to the money laundering risk on the market and to present widespread money laundering techniques and recognizable patterns of abuse. In addition, this paper aims to find an answer to the question to what extent the measures of the fifth EU Anti-Money Laundering Directive (AMLD) as well as other appropriate preventive measures are sufficient to reduce the money laundering risk in the area of virtual currencies (VC).Design/methodology/approachFirstly, the analysis requires a consideration of the theoretical foundations of money laundering methods, as well as a presentation of the technical foundations of cryptocurrencies and their ecosystem. Secondly, it is discussed to what extent VC are suitable for money laundering, which characteristics enable them to launder money and which new money laundering techniques result from this. In addition, a comparison of different money laundering risk classification is done in relation to VC from the perspective of different actors in the financial market.FindingsOwing to their simple electronic storage and transferability, crypto assets pose a concrete risk of money laundering. Their inclusion in the fifth AMLD was therefore a necessary step by the European legislator. However, the question arises to whether the directive and the further preventive measures presented in this paper sufficiently fulfil the objective of reducing the money laundering risk in relation to VC. One positive aspect is the inclusion of the crypto custody business as a financial service in the German Banking Act. According to the definition in Section 1 (1a) sentence 2 no. 6, the offering of wallets is subject to authorization and the offering party becomes an obligated party within the meaning of the Germany Money Laundering Act. From a supervisory point of view, the new licensing requirement is very much welcomed, as the custody of private cryptographic keys entails considerable risks. However, non-custodian wallet providers who do not store the private keys of their users, are not covered. A closer analysis of the amending directive to the fourth EU AMLD reveals that other relevant players in the crypto market, such as mixer and tumbler services, are also not covered.Originality/valueIt is quite clear that cryptocurrencies and the blockchain technology will continue to accompany one in the coming years. Further credit institutions arising in the market exposed to the described risks will be seen. The paper will therefore present and evaluate possible risk reduction/options for anti-money laundering for new and existing financial institutions.

CYBERCRIME AND MONEY LAUNDERING IN 21ST CENTURY

This paper focuses on cybercrime and money laundering. Proceeds of these activities may be used to fund further criminal activities and to undermine the integrity of financial systems worldwide. Money laundering is the biggest method followed by the cyber criminals to hide their black money which they get themselves courtesy to financial frauds they involve into. Money laundering is the process of making large amounts of money generated by a criminal activity, such as drug trafficking or terrorist funding, appear to have come from a legitimate source. The money from the criminal activity is considered dirty, and the process "launders" it to make it look clean.Unlike the "traditional" money laundering methods, which rely on the banking system, cyber-laundering depends on the use of various types of transactions and financial services providers, ranging from wire transfers, cash deposits/withdrawals and e-money transactions to "money mules" and remittance services.

Leveraging machine learning in the global fight against money laundering and terrorism financing: An affordances perspective

Financial services organisations facilitate the movement of money worldwide, and keep records of their clients’ identity and financial behaviour. As such, they have been enlisted by governments worldwide to assist with the detection and prevention of money laundering, which is a key tool in the fight to reduce crime and create sustainable economic development, corresponding to Goal 16 of the United Nations Sustainable Development Goals. In this paper, we investigate how the technical and contextual affordances of machine learning algorithms may enable these organisations to accomplish that task. We find that, due to the unavailability of high-quality, large training datasets regarding money laundering methods, there is limited scope for using supervised machine learning. Conversely, it is possible to use reinforced machine learning and, to an extent, unsupervised learning, although only to model unusual financial behaviour, not actual money laundering.

Стадии и способы легализации преступных доходов, полученных в результате совершения преступлений экономической и налоговой направленности

In this article, based on the study and analysis of operational-search legislation, scientific publications, law enforcement practice and the criminal situation in the field of legalization, the operationalsearch counteraction to the legalization of income received from the Commission of tax crimes is considered. The paper focuses on the stages (stages) of laundering, the existing points of view on this account, as well as on the methods of illegal withdrawal of funds abroad. The author of the article aimed to develop scientifically based proposals and recommendations for improving the effectiveness of this type of activity by the territorial bodies of internal Affairs and their divisions of economic security and anti-corruption. It is proposed to put forward and work out operational search versions within the subject of study, as well as to develop, taking into account the methods (schemes) used by criminals to launder criminal proceeds and illegally withdraw funds abroad for the purpose of their subsequent legalization, operational search measures to document their criminal actions. In addition, the author recommends constant monitoring of money laundering methods based on operational and investigative practices. The results and key conclusions formulated in this article can be used in the theory and practice of operational investigative activities of internal Affairs bodies to counteract the legalization of income received from tax crimes.