The development of virtual currencies,network banking,and artificial intelligence technologies facilitates the implementation and completion of self-money laundering in crimes involving embezzlement and bribery.Amendm...The development of virtual currencies,network banking,and artificial intelligence technologies facilitates the implementation and completion of self-money laundering in crimes involving embezzlement and bribery.Amendment XI to the Criminal Law of the People's Republic of China lists self-money laundering as a separate money laundering crime,breaking the restrictive framework that it must be committed by someone else.This is reflective of the specific interest that China has in anti-money laundering.The criminalization of self-money laundering has been adopted as a powerful legal weapon against money laundering.However,it has confronted a series of dilemmas in terms of specific judicial applications.To gradually address the dilemmas in applying the clause,a comprehensive consideration of Chinese judicial and anti-money laundering practices,as well as international anti-money laundering regulations and practices,is carried out.Moreover,the following recommendations are given:that the protection of legal interests concerning self-money laundering should be expanded appropriately;that a penalty and cooperation system should be established for the crime of self-money laundering;and that the scope of the means of self-money laundering should be extended.展开更多
As financial criminal methods become increasingly sophisticated, traditional anti-money laundering and fraud detection approaches face significant challenges. This study focuses on the application technologies and cha...As financial criminal methods become increasingly sophisticated, traditional anti-money laundering and fraud detection approaches face significant challenges. This study focuses on the application technologies and challenges of big data analytics in anti-money laundering and financial fraud detection. The research begins by outlining the evolutionary trends of financial crimes and highlighting the new characteristics of the big data era. Subsequently, it systematically analyzes the application of big data analytics technologies in this field, including machine learning, network analysis, and real-time stream processing. Through case studies, the research demonstrates how these technologies enhance the accuracy and efficiency of anomalous transaction detection. However, the study also identifies challenges faced by big data analytics, such as data quality issues, algorithmic bias, and privacy protection concerns. To address these challenges, the research proposes solutions from both technological and managerial perspectives, including the application of privacy-preserving technologies like federated learning. Finally, the study discusses the development prospects of Regulatory Technology (RegTech), emphasizing the importance of synergy between technological innovation and regulatory policies. This research provides guidance for financial institutions and regulatory bodies in optimizing their anti-money laundering and fraud detection strategies.展开更多
The purpose of this paper is to provide an economic overview of the costs and benefits of anti-money laundering （AML） rules. After defining and explaining the three stages of money laundering, the paper provides an ...The purpose of this paper is to provide an economic overview of the costs and benefits of anti-money laundering （AML） rules. After defining and explaining the three stages of money laundering, the paper provides an insight into the volume and development of money laundering activities in the Central and Eastern Europe. It relies on international, comparative studies outlines the impact of AML measures on banks and other financial intermediaries Conditions of reporting suspicious activity and government agencies, which use these reports to identify investigation targets, are also analysed. Moreover, the paper discusses possible reasons for the failure of AML rules to fight against the crimes and collateral damage caused by AML. These figures, which are presented in this scientific research, give an indication of how important the money laundering problem and the level of organized crime are.展开更多
The main purpose of this study is to develop a mathematical model for calculating the probability of money laundering process, by monitoring the behavior of the client using 70 indicators of money laundering. The scie...The main purpose of this study is to develop a mathematical model for calculating the probability of money laundering process, by monitoring the behavior of the client using 70 indicators of money laundering. The scientific method used in this study （received from the Modern Criminology） has great investigative power and it is widely applicable. Hopefully the practical application of this study will increase greatly the probability of detection and punishment of the clients who are implicated in the process of money laundering. In particular, this study will be useful for banks, Financial Intelligence Unit （FIU） of Albania, Department of Economic Crime at the Ministry of Domestic Affairs and Albanian State Intelligence Service （SIS）. Also, the investigation of money laundering will be a useful tool to detect other crimes, such as drug trafficking, human trafficking, illegal arms trade, etc. The prevention of money laundering is simultaneously a powerful strike against terrorism both on national and international levels.展开更多
Considering the constantly increasing of data in large databases such as wire transfer database, incremental clustering algorithms play a more and more important role in Data Mining （DM）. However, Few of the traditi...Considering the constantly increasing of data in large databases such as wire transfer database, incremental clustering algorithms play a more and more important role in Data Mining （DM）. However, Few of the traditional clustering algorithms can not only handle the categorical data, but also explain its output clearly. Based on the idea of dynamic clustering, an incremental conceptive clustering algorithm is proposed in this paper. Which introduces the Semantic Core Tree （SCT） to deal with large volume of categorical wire transfer data for the detecting money laundering. In addition, the rule generation algorithm is presented here to express the clustering result by the format of knowledge. When we apply this idea in financial data mining, the efficiency of searching the characters of money laundering data will be improved.展开更多
Effective link analysis techniques are needed to help law enforcement and intelligence agencies fight money laundering. This paper presents a link analysis technique that uses a modified shortest-path algorithms to id...Effective link analysis techniques are needed to help law enforcement and intelligence agencies fight money laundering. This paper presents a link analysis technique that uses a modified shortest-path algorithms to identify the strongest association paths between entities in a money laundering network. Based on two-tree Dijkstra and Priority＇First-Search （PFS） algorithm, a modified algorithm is presented. To apply the algorithm, a network representation transformation is made first.展开更多
This study aimed at identifying the role and importance of internal control procedures for detecting and preventing money laundering operations in banks through defining the internal control procedures which contribut...This study aimed at identifying the role and importance of internal control procedures for detecting and preventing money laundering operations in banks through defining the internal control procedures which contribute to detecting money laundering operations. These procedures include the guide and policies issued by the administration of banks in order to combat laundering money operations as well as to train employees on matters pertaining to the money laundering operations. The study showed the role of the internal control procedures in detecting practically the money laundering through the automated programs and the system of saving the files and records. Furthermore, the study showed the factors affecting the internal control procedures to anti-money laundering operations. The researcher used an analytical descriptive approach for collecting data which relate to the main elements of the study, analyzing and explaining them. This study aimed at building the theoretical framework depending on audit literature which addressed internal control system, anti-money laundering systems, and control procedures of anti-money laundering. Through the theoretical framework, a questionnaire related to the application of internal control procedures and its relation to anti-money laundering operations was designed. It was distributed to the population of the study which includes internal and external auditors and the head of anti-money laundering operations unit in the Jordanian banks. The study found that applying internal control procedures is important for detecting and preventing money laundering operations in the Jordanian banks and that there are factors affecting the nature and the extent of internal control standards pertaining to anti-money laundering operations in the Jordanian banks.展开更多
This study is the first attempt to investigate the relationship between the annual GDP growth rate and money laundering in the Republic of Albania during the period 2007-2011. The main result of the study: there is a ...This study is the first attempt to investigate the relationship between the annual GDP growth rate and money laundering in the Republic of Albania during the period 2007-2011. The main result of the study: there is a negative correlation between money laundering process and economic growth rate in Albania during the specified period;there is a negative correlation between money laundering and import, but there is a positive correlation between money laundering and the government expenditure, as well a positive correlation between money laundering and export.展开更多
The effect of extended laundering on cotton fabric treated with Dimethylol dihydroxyethyleneurea (DMDHEU) easy care finish was investigated and the fabric characterised by crease recovery performance and the Kawabata ...The effect of extended laundering on cotton fabric treated with Dimethylol dihydroxyethyleneurea (DMDHEU) easy care finish was investigated and the fabric characterised by crease recovery performance and the Kawabata Evaluation System for Fabrics (KES-F). The KES-F results indicated that the mechanical handle properties of the DMDHEU treated cotton fabrics were affected by both the levels of application of the DMDHEU easy care finishes and the stress relaxation of the fabrics in aqueous conditions.展开更多
The aim of this work was to investigate the electrical resistance change of electro-textiles manufactured using cotton fabrics with stainless steel and silver plated PA yarns incorporation after being subjected to hom...The aim of this work was to investigate the electrical resistance change of electro-textiles manufactured using cotton fabrics with stainless steel and silver plated PA yarns incorporation after being subjected to home laundering, i.e. detergent washing and silicone softening. Electrical resistances of conductive yams inside the fabric structure were compared and discussed statistically before and after washing and softener application. Greatest changes in electrical resistances were observed with samples including silver plated PA yams. After five washing cycles with detergent, silicone softening agent is removed from yarns by washing, and thus conductivity increases. Further washing of e-textiles with detergent for five more cycles causes decrease in conductivity, because of chemical effects of detergent and mechanical effects of washing process such as abrasion due to friction. Detergent which has negative reactive sites bonds with metal ions reduces conductivity.展开更多
Finding the best method to assess the effectiveness of Anti-Money Laundering(AML)policies is a controversial issue. Based on about 9,000 questionnaires circulated to AML professionals and other related staff at the Pe...Finding the best method to assess the effectiveness of Anti-Money Laundering(AML)policies is a controversial issue. Based on about 9,000 questionnaires circulated to AML professionals and other related staff at the People's Bank of China and other banking institutions,this study acquired first-hand data from respondents and has resulted in the following key findings:The effectiveness of the whole AML system is rated as"largely effective"in respect to China’s legislation,regulation and supervision,suspicious transaction monitoring and analyses and administrative investigation;the system is rated as"basically effective"in respect to money-laundering prosecutions and convictions and international cooperation.Financial institutions'compliance with AML regulations is rated as"largely effective"in respect to internal control,customer identification,large-value transaction and suspicious transaction reporting,and the record-keeping of ID information and transactions.Statistically,58.48%of respondents said they think that China’s AML regime is"completely effective"or"largely effective;"35.21%say it is"basically effective,"and the remaining 4.68% call it"largely ineffective"or"completely ineffective."The authors conclude by proposing some policy recommendations to enhance the effectiveness of AML policy.展开更多
With the gradual application of central bank digital currency(CBDC)in China,it brings new payment methods,but also potentially derives new money laundering paths.Two typical application scenarios of CBDC are considere...With the gradual application of central bank digital currency(CBDC)in China,it brings new payment methods,but also potentially derives new money laundering paths.Two typical application scenarios of CBDC are considered,namely the anonymous transaction scenario and real-name transaction scenario.First,starting from the interaction network of transactional groups,the degree distribution,density,and modularity of normal and money laundering transactions in two transaction scenarios are compared and analyzed,so as to clarify the characteristics and paths of money laundering transactions.Then,according to the two typical application scenarios,different transaction datasets are selected,and different models are used to train the models on the recognition of money laundering behaviors in the two datasets.Among them,in the anonymous transaction scenario,the graph convolutional neural network is used to identify the spatial structure,the recurrent neural network is fused to obtain the dynamic pattern,and the model ChebNet-GRU is constructed.The constructed ChebNet-GRU model has the best effect in the recognition of money laundering behavior,with a precision of 94.3%,a recall of 59.5%,an F1 score of 72.9%,and a microaverage F1 score of 97.1%.While in the real-name transaction scenario,the traditional machine learning method is far better than the deep learning method,and the micro-average F1 score of the random forest and XGBoost models both reach 99.9%,which can effectively identify money laundering in currency transactions.展开更多
Due to its anonymity and decentralization,Bitcoin has long been a haven for various illegal activities.Cybercriminals generally legalize illicit funds by Bitcoin mixing services.Therefore,it is critical to investigate...Due to its anonymity and decentralization,Bitcoin has long been a haven for various illegal activities.Cybercriminals generally legalize illicit funds by Bitcoin mixing services.Therefore,it is critical to investigate the mixing services in cryptocurrency anti-money laundering.Existing studies treat different mixing services as a class of suspicious Bitcoin entities.Furthermore,they are limited by relying on expert experience or needing to deal with large-scale networks.So far,multi-class mixing service identification has not been explored yet.It is challenging since mixing services share a similar procedure,presenting no sharp distinctions.However,mixing service identification facilitates the healthy development of Bitcoin,supports financial forensics for cryptocurrency regulation and legislation,and provides technical means for fine-grained blockchain supervision.This paper aims to achieve multi-class Bitcoin Mixing Service Identification with a Graph Classification(BMSI-GC)model.First,BMSI-GC constructs 2-hop ego networks(2-egonets)of mixing services based on their historical transactions.Second,it applies graph2vec,a graph classification model mainly used to calculate the similarity between graphs,to automatically extract address features from the constructed 2-egonets.Finally,it trains a multilayer perceptron classifier to perform classification based on the extracted features.BMSI-GC is flexible without handling the full-size network and handcrafting address features.Moreover,the differences in transaction patterns of mixing services reflected in the 2-egonets provide adequate information for identification.Our experimental study demonstrates that BMSI-GC performs excellently in multi-class Bitcoin mixing service identification,achieving an average identification F1-score of 95.08%.展开更多
This study analyzes the impact of a newly emerging type of anti-money laundering regulation that obligates cryptocurrency exchanges to report suspicious transactions to financial authorities.We build a theoretical mod...This study analyzes the impact of a newly emerging type of anti-money laundering regulation that obligates cryptocurrency exchanges to report suspicious transactions to financial authorities.We build a theoretical model for the reporting decision structure of a private bank or cryptocurrency exchange and show that an inferior ability to detect money laundering(ML)increases the ratio of reported transactions to unreported transactions.If a representative money launderer makes an optimal portfolio choice,then this ratio increases further.Our findings suggest that cryptocurrency exchanges will exhibit more excessive reporting behavior under this regulation than private banks.We attribute this result to cryptocurrency exchanges’inferior ML detection abilities and their proximity to the underground economy.展开更多
As a follow-up research of the work on the natural viscosity of turbulence of Huang et al. [Journal of Turbulence(2003)], here we investigate the thixotropic effect of a turbulent Newtonian fluid on the basis of the e...As a follow-up research of the work on the natural viscosity of turbulence of Huang et al. [Journal of Turbulence(2003)], here we investigate the thixotropic effect of a turbulent Newtonian fluid on the basis of the ensemble-averaged Navier–Stokes equation. In view of the natural viscosity, we show that in homogeneous isotropic turbulence the turbulent Newtonian fluid behaves like a thixotropic fluid, exhibiting the thixotropic effect with its natural viscosity decreasing with time.展开更多
The launderability of wool fabrics treated by nano finoshing agent influences directly the functional endurance of he treated wool fabric. In order to investigate the effect of wool fibers surface modification on the ...The launderability of wool fabrics treated by nano finoshing agent influences directly the functional endurance of he treated wool fabric. In order to investigate the effect of wool fibers surface modification on the functional erdurance of nano finishinp wool fibers, in this paper, for the first time wool fibers were chemically modified by using NaClO aqueous and KMnO4 aqueous, and then chemically modified wool fibers and native wool fibers were treated using nano ZnO finishing agent, respectively. The launderability of wool fibers treated by nano finishing agent was investigated. The experimental results show that the chemically modified wool fibers have a good launderaility after being treated by nano ZnO finishing agent treating. The surface morphologies of wool fibers were observed by using SEM. It is got that there is a strong adbesion between nano ZnO and wool surface through XPS analysis.展开更多
Blockchain-based cryptocurrencies,such as Bitcoins,are increasingly popular.However,the decentralized and anonymous nature of these currencies can also be(ab)used for nefarious activities such as money laundering,thus...Blockchain-based cryptocurrencies,such as Bitcoins,are increasingly popular.However,the decentralized and anonymous nature of these currencies can also be(ab)used for nefarious activities such as money laundering,thus reinforcing the importance of designing tools to effectively detect malicious transaction misbehaviors.In this paper,we propose TMAS,a transaction misbehavior analysis scheme for blockchain-based cryptocurrencies.Specifically,the proposed system includes ten features in the transaction graph,two heuristic money laundering models,and an analysis method for account linkage,which identifies accounts that are distinct but controlled by an identical entity.To evaluate the effectiveness of our proposed indicators and models,we analyze 100 million transactions and compute transaction features,and are able to identify a number of suspicious accounts.Moreover,the proposed methods can be applied to other cryptocurrencies,such as token-based cryptocurrencies(e.g.,Bitcoins)and account-based cryptocurrencies(e.g.,Ethereum).展开更多
Fighting financial crime is a highly institutionalised global governance task.At a time of crisis for many of the institutions of global governance,tackling money laundering and combatting terrorist financing through ...Fighting financial crime is a highly institutionalised global governance task.At a time of crisis for many of the institutions of global governance,tackling money laundering and combatting terrorist financing through global cooperation continues to be a priority for public officials.The global regime,if anything,is intensifying.This essay provides an overview of the regime’s development and addresses questions of design and implementation.It is structured around three sets of questions:(1)What does the regime look like and what is it for?(2)Who does the work?(3)And,in conclusion,what can we say about winners and losers?展开更多
基金The project is the phased achievement of the National Scholarship Fund"National Construction High-level University Graduate Program"(No.CSC 202206040074)。
文摘The development of virtual currencies,network banking,and artificial intelligence technologies facilitates the implementation and completion of self-money laundering in crimes involving embezzlement and bribery.Amendment XI to the Criminal Law of the People's Republic of China lists self-money laundering as a separate money laundering crime,breaking the restrictive framework that it must be committed by someone else.This is reflective of the specific interest that China has in anti-money laundering.The criminalization of self-money laundering has been adopted as a powerful legal weapon against money laundering.However,it has confronted a series of dilemmas in terms of specific judicial applications.To gradually address the dilemmas in applying the clause,a comprehensive consideration of Chinese judicial and anti-money laundering practices,as well as international anti-money laundering regulations and practices,is carried out.Moreover,the following recommendations are given:that the protection of legal interests concerning self-money laundering should be expanded appropriately;that a penalty and cooperation system should be established for the crime of self-money laundering;and that the scope of the means of self-money laundering should be extended.
文摘As financial criminal methods become increasingly sophisticated, traditional anti-money laundering and fraud detection approaches face significant challenges. This study focuses on the application technologies and challenges of big data analytics in anti-money laundering and financial fraud detection. The research begins by outlining the evolutionary trends of financial crimes and highlighting the new characteristics of the big data era. Subsequently, it systematically analyzes the application of big data analytics technologies in this field, including machine learning, network analysis, and real-time stream processing. Through case studies, the research demonstrates how these technologies enhance the accuracy and efficiency of anomalous transaction detection. However, the study also identifies challenges faced by big data analytics, such as data quality issues, algorithmic bias, and privacy protection concerns. To address these challenges, the research proposes solutions from both technological and managerial perspectives, including the application of privacy-preserving technologies like federated learning. Finally, the study discusses the development prospects of Regulatory Technology (RegTech), emphasizing the importance of synergy between technological innovation and regulatory policies. This research provides guidance for financial institutions and regulatory bodies in optimizing their anti-money laundering and fraud detection strategies.
文摘The purpose of this paper is to provide an economic overview of the costs and benefits of anti-money laundering （AML） rules. After defining and explaining the three stages of money laundering, the paper provides an insight into the volume and development of money laundering activities in the Central and Eastern Europe. It relies on international, comparative studies outlines the impact of AML measures on banks and other financial intermediaries Conditions of reporting suspicious activity and government agencies, which use these reports to identify investigation targets, are also analysed. Moreover, the paper discusses possible reasons for the failure of AML rules to fight against the crimes and collateral damage caused by AML. These figures, which are presented in this scientific research, give an indication of how important the money laundering problem and the level of organized crime are.
文摘The main purpose of this study is to develop a mathematical model for calculating the probability of money laundering process, by monitoring the behavior of the client using 70 indicators of money laundering. The scientific method used in this study （received from the Modern Criminology） has great investigative power and it is widely applicable. Hopefully the practical application of this study will increase greatly the probability of detection and punishment of the clients who are implicated in the process of money laundering. In particular, this study will be useful for banks, Financial Intelligence Unit （FIU） of Albania, Department of Economic Crime at the Ministry of Domestic Affairs and Albanian State Intelligence Service （SIS）. Also, the investigation of money laundering will be a useful tool to detect other crimes, such as drug trafficking, human trafficking, illegal arms trade, etc. The prevention of money laundering is simultaneously a powerful strike against terrorism both on national and international levels.
基金Supported by the National Natural Science Foun-dation of China (60403027) the Natural Science Foundation of HubeiProvince (2005ABA258)the Opening Foundation of State KeyLaboratory of Software Engineering (SKLSE05-07)
文摘Considering the constantly increasing of data in large databases such as wire transfer database, incremental clustering algorithms play a more and more important role in Data Mining （DM）. However, Few of the traditional clustering algorithms can not only handle the categorical data, but also explain its output clearly. Based on the idea of dynamic clustering, an incremental conceptive clustering algorithm is proposed in this paper. Which introduces the Semantic Core Tree （SCT） to deal with large volume of categorical wire transfer data for the detecting money laundering. In addition, the rule generation algorithm is presented here to express the clustering result by the format of knowledge. When we apply this idea in financial data mining, the efficiency of searching the characters of money laundering data will be improved.
基金Supported bythe National Tenth Five-Year PlanforScientific and Technological Development of China (2001BA102A06-11)
文摘Effective link analysis techniques are needed to help law enforcement and intelligence agencies fight money laundering. This paper presents a link analysis technique that uses a modified shortest-path algorithms to identify the strongest association paths between entities in a money laundering network. Based on two-tree Dijkstra and Priority＇First-Search （PFS） algorithm, a modified algorithm is presented. To apply the algorithm, a network representation transformation is made first.
文摘This study aimed at identifying the role and importance of internal control procedures for detecting and preventing money laundering operations in banks through defining the internal control procedures which contribute to detecting money laundering operations. These procedures include the guide and policies issued by the administration of banks in order to combat laundering money operations as well as to train employees on matters pertaining to the money laundering operations. The study showed the role of the internal control procedures in detecting practically the money laundering through the automated programs and the system of saving the files and records. Furthermore, the study showed the factors affecting the internal control procedures to anti-money laundering operations. The researcher used an analytical descriptive approach for collecting data which relate to the main elements of the study, analyzing and explaining them. This study aimed at building the theoretical framework depending on audit literature which addressed internal control system, anti-money laundering systems, and control procedures of anti-money laundering. Through the theoretical framework, a questionnaire related to the application of internal control procedures and its relation to anti-money laundering operations was designed. It was distributed to the population of the study which includes internal and external auditors and the head of anti-money laundering operations unit in the Jordanian banks. The study found that applying internal control procedures is important for detecting and preventing money laundering operations in the Jordanian banks and that there are factors affecting the nature and the extent of internal control standards pertaining to anti-money laundering operations in the Jordanian banks.
文摘This study is the first attempt to investigate the relationship between the annual GDP growth rate and money laundering in the Republic of Albania during the period 2007-2011. The main result of the study: there is a negative correlation between money laundering process and economic growth rate in Albania during the specified period;there is a negative correlation between money laundering and import, but there is a positive correlation between money laundering and the government expenditure, as well a positive correlation between money laundering and export.
文摘The effect of extended laundering on cotton fabric treated with Dimethylol dihydroxyethyleneurea (DMDHEU) easy care finish was investigated and the fabric characterised by crease recovery performance and the Kawabata Evaluation System for Fabrics (KES-F). The KES-F results indicated that the mechanical handle properties of the DMDHEU treated cotton fabrics were affected by both the levels of application of the DMDHEU easy care finishes and the stress relaxation of the fabrics in aqueous conditions.
文摘The aim of this work was to investigate the electrical resistance change of electro-textiles manufactured using cotton fabrics with stainless steel and silver plated PA yarns incorporation after being subjected to home laundering, i.e. detergent washing and silicone softening. Electrical resistances of conductive yams inside the fabric structure were compared and discussed statistically before and after washing and softener application. Greatest changes in electrical resistances were observed with samples including silver plated PA yams. After five washing cycles with detergent, silicone softening agent is removed from yarns by washing, and thus conductivity increases. Further washing of e-textiles with detergent for five more cycles causes decrease in conductivity, because of chemical effects of detergent and mechanical effects of washing process such as abrasion due to friction. Detergent which has negative reactive sites bonds with metal ions reduces conductivity.
文摘Finding the best method to assess the effectiveness of Anti-Money Laundering(AML)policies is a controversial issue. Based on about 9,000 questionnaires circulated to AML professionals and other related staff at the People's Bank of China and other banking institutions,this study acquired first-hand data from respondents and has resulted in the following key findings:The effectiveness of the whole AML system is rated as"largely effective"in respect to China’s legislation,regulation and supervision,suspicious transaction monitoring and analyses and administrative investigation;the system is rated as"basically effective"in respect to money-laundering prosecutions and convictions and international cooperation.Financial institutions'compliance with AML regulations is rated as"largely effective"in respect to internal control,customer identification,large-value transaction and suspicious transaction reporting,and the record-keeping of ID information and transactions.Statistically,58.48%of respondents said they think that China’s AML regime is"completely effective"or"largely effective;"35.21%say it is"basically effective,"and the remaining 4.68% call it"largely ineffective"or"completely ineffective."The authors conclude by proposing some policy recommendations to enhance the effectiveness of AML policy.
基金supported by the National Science Foundation of China(No.61602536)the Emerging Interdisciplinary Project of Central University of Finance and Economics(CUFE),and Financial Sustainable Development Research Team.
文摘With the gradual application of central bank digital currency(CBDC)in China,it brings new payment methods,but also potentially derives new money laundering paths.Two typical application scenarios of CBDC are considered,namely the anonymous transaction scenario and real-name transaction scenario.First,starting from the interaction network of transactional groups,the degree distribution,density,and modularity of normal and money laundering transactions in two transaction scenarios are compared and analyzed,so as to clarify the characteristics and paths of money laundering transactions.Then,according to the two typical application scenarios,different transaction datasets are selected,and different models are used to train the models on the recognition of money laundering behaviors in the two datasets.Among them,in the anonymous transaction scenario,the graph convolutional neural network is used to identify the spatial structure,the recurrent neural network is fused to obtain the dynamic pattern,and the model ChebNet-GRU is constructed.The constructed ChebNet-GRU model has the best effect in the recognition of money laundering behavior,with a precision of 94.3%,a recall of 59.5%,an F1 score of 72.9%,and a microaverage F1 score of 97.1%.While in the real-name transaction scenario,the traditional machine learning method is far better than the deep learning method,and the micro-average F1 score of the random forest and XGBoost models both reach 99.9%,which can effectively identify money laundering in currency transactions.
基金supported in part by National Key R&D Program of China under Grant 2023YFB3106801in part by Jiangsu Province Natural Science Foundation Project under Grant BK20231413+1 种基金in part by the National Natural Science Foundation of China under Grants 61602114 and 62172093in part by the Special Funds for Basic Scientific Research Operations of Central Universities under Grant 2242024K30021。
文摘Due to its anonymity and decentralization,Bitcoin has long been a haven for various illegal activities.Cybercriminals generally legalize illicit funds by Bitcoin mixing services.Therefore,it is critical to investigate the mixing services in cryptocurrency anti-money laundering.Existing studies treat different mixing services as a class of suspicious Bitcoin entities.Furthermore,they are limited by relying on expert experience or needing to deal with large-scale networks.So far,multi-class mixing service identification has not been explored yet.It is challenging since mixing services share a similar procedure,presenting no sharp distinctions.However,mixing service identification facilitates the healthy development of Bitcoin,supports financial forensics for cryptocurrency regulation and legislation,and provides technical means for fine-grained blockchain supervision.This paper aims to achieve multi-class Bitcoin Mixing Service Identification with a Graph Classification(BMSI-GC)model.First,BMSI-GC constructs 2-hop ego networks(2-egonets)of mixing services based on their historical transactions.Second,it applies graph2vec,a graph classification model mainly used to calculate the similarity between graphs,to automatically extract address features from the constructed 2-egonets.Finally,it trains a multilayer perceptron classifier to perform classification based on the extracted features.BMSI-GC is flexible without handling the full-size network and handcrafting address features.Moreover,the differences in transaction patterns of mixing services reflected in the 2-egonets provide adequate information for identification.Our experimental study demonstrates that BMSI-GC performs excellently in multi-class Bitcoin mixing service identification,achieving an average identification F1-score of 95.08%.
文摘This study analyzes the impact of a newly emerging type of anti-money laundering regulation that obligates cryptocurrency exchanges to report suspicious transactions to financial authorities.We build a theoretical model for the reporting decision structure of a private bank or cryptocurrency exchange and show that an inferior ability to detect money laundering(ML)increases the ratio of reported transactions to unreported transactions.If a representative money launderer makes an optimal portfolio choice,then this ratio increases further.Our findings suggest that cryptocurrency exchanges will exhibit more excessive reporting behavior under this regulation than private banks.We attribute this result to cryptocurrency exchanges’inferior ML detection abilities and their proximity to the underground economy.
文摘As a follow-up research of the work on the natural viscosity of turbulence of Huang et al. [Journal of Turbulence(2003)], here we investigate the thixotropic effect of a turbulent Newtonian fluid on the basis of the ensemble-averaged Navier–Stokes equation. In view of the natural viscosity, we show that in homogeneous isotropic turbulence the turbulent Newtonian fluid behaves like a thixotropic fluid, exhibiting the thixotropic effect with its natural viscosity decreasing with time.
文摘The launderability of wool fabrics treated by nano finoshing agent influences directly the functional endurance of he treated wool fabric. In order to investigate the effect of wool fibers surface modification on the functional erdurance of nano finishinp wool fibers, in this paper, for the first time wool fibers were chemically modified by using NaClO aqueous and KMnO4 aqueous, and then chemically modified wool fibers and native wool fibers were treated using nano ZnO finishing agent, respectively. The launderability of wool fibers treated by nano finishing agent was investigated. The experimental results show that the chemically modified wool fibers have a good launderaility after being treated by nano ZnO finishing agent treating. The surface morphologies of wool fibers were observed by using SEM. It is got that there is a strong adbesion between nano ZnO and wool surface through XPS analysis.
基金supported by the Fujian Key Labo-ratory of Financial Information Processing(Putian University)(No.JXC202304)Yunnan Key Laboratory of Block-chain Application Tech-nology(No.202305AG340008)+1 种基金the Opening Project of Nanchang In-novation Institute,Peking University(No.NCII2022A02)Science and Technology Project of Putian City(No.2021R4001-10).The work of K.-K.R.Choo was supported only by the Cloud Technology Endowed Professorship.
文摘Blockchain-based cryptocurrencies,such as Bitcoins,are increasingly popular.However,the decentralized and anonymous nature of these currencies can also be(ab)used for nefarious activities such as money laundering,thus reinforcing the importance of designing tools to effectively detect malicious transaction misbehaviors.In this paper,we propose TMAS,a transaction misbehavior analysis scheme for blockchain-based cryptocurrencies.Specifically,the proposed system includes ten features in the transaction graph,two heuristic money laundering models,and an analysis method for account linkage,which identifies accounts that are distinct but controlled by an identical entity.To evaluate the effectiveness of our proposed indicators and models,we analyze 100 million transactions and compute transaction features,and are able to identify a number of suspicious accounts.Moreover,the proposed methods can be applied to other cryptocurrencies,such as token-based cryptocurrencies(e.g.,Bitcoins)and account-based cryptocurrencies(e.g.,Ethereum).
文摘Fighting financial crime is a highly institutionalised global governance task.At a time of crisis for many of the institutions of global governance,tackling money laundering and combatting terrorist financing through global cooperation continues to be a priority for public officials.The global regime,if anything,is intensifying.This essay provides an overview of the regime’s development and addresses questions of design and implementation.It is structured around three sets of questions:(1)What does the regime look like and what is it for?(2)Who does the work?(3)And,in conclusion,what can we say about winners and losers?
