Article
Business
Eray Arda Akartuna, Shane D. Johnson, Amy Thornton
Summary: This study explores the impact of financial innovation and technological advances on money laundering and terrorist financing risks. Criminals are taking advantage of security vulnerabilities in distributed ledger technologies, new payment methods, and financial technology to engage in illicit activities. The current detection-based approach can be supplemented with diverse countermeasures to increase effectiveness. However, the specific circumstances and constraints of different stakeholders will affect their ability to implement these measures.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Computer Science, Artificial Intelligence
Rasmus Ingemann Tuffveson Jensen, Alexandros Iosifidis
Summary: We propose a deep learning approach to enhance anti-money laundering alarms in banks by automatically extracting latent features from transaction sequences. Our experiments demonstrate that the best model, which uses gated recurrent units and self-attention, can significantly reduce false positives while raising new alarms for high-risk clients without traditional alarm inquiries.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Ling Sun
Summary: This article discusses the research and implementation of security control in the anti-money laundering monitoring and analysis system, focusing on the application of decision tree analysis technology in insurance companies to enhance their anti-money laundering monitoring capabilities. The use of data mining technology provides a new system solution for anti-money laundering monitoring, especially in identifying potential money laundering cases in suspicious and large transactions. The decision tree analysis technology significantly improves security monitoring capabilities in the insurance sector, with experimental data showing high accuracy rates in customer classification and transaction monitoring.
Article
Business
Destan Kirimhan
Summary: This study highlights the significance of AML regulations in establishing cybersecurity among prosumers in decentralized finance (DeFi). Using a game theory model based on crime theories, the study reveals that the benefits of financial inclusivity and pseudonymity in permissionless DeFi come at the cost of vulnerability to cyberattacks due to non-compliance with AML regulations. In contrast, AML-compliant permissioned DeFi can deter cyberattackers. These findings have important implications for trust within the context of blockchain-based sharing economy and the role of decentralized governance and smart contract auditors in maintaining cybersecurity while ensuring trust. The study also suggests cybersecurity policies for permissionless DeFi without compromising its decentralized nature.
JOURNAL OF BUSINESS RESEARCH
(2023)
Review
Business, Finance
D. Bartolozzi, M. Gara, D. J. Marchetti, D. Masciandaro
Summary: Using a unique data set, this paper examines the governance of Financial Intelligence Units (FIUs), which are anti-money laundering (AML) supervisors. The study explores the factors that drive the governance of FIUs and finds that financial powers of FIUs are weaker in bank-based economies and stronger in countries with affiliations to international AML organizations. Additionally, the study reveals that FIUs' law enforcement powers are more intense in civil law countries, and that Islamic culture also plays a role in the choice of FIU type. The overall FIU Governance Index is stronger in more developed and transparent countries. Lastly, the study finds that both overall FIU governance and independence and accountability are weaker in countries with law enforcement FIUs.
INTERNATIONAL REVIEW OF ECONOMICS & FINANCE
(2022)
Article
Business, Finance
Isaac Ofoeda, Elikplimi K. Agbloyor, Joshua Y. Abor, Kofi A. Osei
Summary: This paper examines the impact of anti-money laundering regulations on financial sector development globally. The study finds that these regulations generally promote financial sector development, with a stronger effect observed in developing countries. The research also identifies a threshold effect of anti-money laundering regulations, where the positive impact is concentrated below a certain threshold value.
INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS
(2022)
Article
Computer Science, Information Systems
Jiayi Liu, Changchun Yin, Hao Wang, Xiaofei Wu, Dongwan Lan, Lu Zhou, Chunpeng Ge
Summary: The number and amount of money laundering crimes for Ethereum have been exponentially increasing in recent years. However, previous studies fail to differentiate money laundering from other malicious activities, resulting in a lack of accurate money laundering detection. In this paper, we propose GTN2vec, an improved graph embedding algorithm specifically designed to detect money laundering activities. By mining Ethereum transaction records, GTN2vec comprehensively considers the behavioral patterns of money launderers and the structural information of transaction networks, effectively extracting features of money laundering addresses. Experimental results demonstrate that GTN2vec outperforms other advanced graph embedding methods in accurately and effectively detecting money laundering accounts.
Article
Computer Science, Cybernetics
Fangfang Zhou, Yunpeng Chen, Chunyao Zhu, Lijia Jiang, Xincheng Liao, Zengsheng Zhong, Xiaohui Chen, Yi Chen, Ying Zhao
Summary: This study investigates new solutions for anti-money laundering in cryptocurrency exchanges by proposing a visual analysis approach that detects suspicious money laundering accounts and visualizes the algorithm results and relevant transaction data.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Ahmed N. Bakry, Almohammady S. Alsharkawy, Mohamed S. Farag, K. R. Raslan
Summary: This paper proposes an automatic suppression-based framework called ASXAML for anti-money laundering, which enhances detection by reducing false positives, and achieves good results.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Multidisciplinary Sciences
Rasmus Ingemann Tuffveson Jensen, Joras Ferwerda, Kristian Sand Jorgensen, Erik Rathje Jensen, Martin Borg, Morten Persson Krogh, Jonas Brunholm Jensen, Alexandros Iosifidis
Summary: Due to the confidentiality of bank transactions, there is a lack of public data sets for investigating and comparing anti-money laundering methods in banks, which severely limits research in this area. To address this issue, we propose SynthAML, a synthetic data set for benchmarking statistical and machine learning methods for AML, and analyze open problems in the AML literature.
Article
Business, Finance
Emily Fletcher, Charles Larkin, Shaen Corbet
Summary: Bitcoin was created to cater to the under-banked and un-banked in regions with inefficient financial systems, but it has been exploited by criminals and terrorists for illicit activities. Governments' reactions to Bitcoin vary from bans to tolerance, and disagreements on its classification have led to bureaucratic conflicts. Some suggest classifying Bitcoin as a technology and entrust regulation to private sector technology companies.
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE
(2021)
Article
Computer Science, Information Systems
Ammar Oad, Abdul Razaque, Askar Tolemyssov, Munif Alotaibi, Bandar Alotaibi, Chenglin Zhao
Summary: The paper introduces a blockchain-enabled transaction scanning method for detecting anomalous actions in transactions and restricting malicious activities through specified rules. Experimental results demonstrate that the method automates the process of investigating transactions and effectively restricts money laundering incidents.
Article
Business, Finance
Arjan Premti, Mohammad Jafarinejad, Henry Balani
Summary: Research shows that the Fourth Anti-Money Laundering Directive had a positive valuation effect on European banks, helping to reduce systematic risk. The extent of this effect was influenced by factors such as a bank's riskiness, size, profitability, as well as the country it operates in.
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE
(2021)
Article
Business
Henry Ogbeide, Mary Elizabeth Thomson, Mustafa Sinan Gonul, Andrew Castairs Pollock, Sanjay Bhowmick, Abdullahi Usman Bello
Summary: Since the 1980s, research and practice have explored the vulnerabilities of financial institutions to money laundering risk and offered insights on how experts conduct anti-money laundering risk assessments. One common theme in the literature is the emphasis on box-ticking over judgment, raising questions about whether experts are immune to cognitive biases that novices are vulnerable to during risk assessment. Both experts and novices displayed overconfidence in their judgments, with the effect being slightly more pronounced in the expert group. Novices slightly outperformed experts in terms of correct outcomes. An effective feedback mechanism could help experts in this field alleviate biases, improve processes, and enhance judgment accuracy.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Business, Finance
Guike Zhang, Zengan Gao, June Dong, Dexiang Mei
Summary: This paper proposes a methodology for constructing the national anti-money laundering (AML) index based on Mutual Evaluation reports and machine learning models. The random forests five-factor (RF-FF) model has high prediction accuracy and good out-of-sample predictive ability for the MER-AML index, significantly outperforming competing models. The time-series national AML index constructed based on the RF-FF model provides new perspectives on measuring AML systems and facilitates empirical studies related to evaluating the controversial AML regime.
FINANCE RESEARCH LETTERS
(2023)
Article
Information Science & Library Science
Dionysios S. Demetis, Allen S. Lee
INFORMATION AND ORGANIZATION
(2016)
Article
Criminology & Penology
Dionysios S. Demetis
JOURNAL OF MONEY LAUNDERING CONTROL
(2009)
Article
Criminology & Penology
Dionysios S. Demetis, Ian O. Angell
JOURNAL OF MONEY LAUNDERING CONTROL
(2007)
Article
Criminology & Penology
Dionysios S. Demetis, Ian O. Angell
JOURNAL OF MONEY LAUNDERING CONTROL
(2006)
Article
Criminology & Penology
Ian O. Angell, Dionysios S. Demetis
JOURNAL OF MONEY LAUNDERING CONTROL
(2005)
