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
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
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
针对国内外金融领域可疑交易的低检测率问题,通过对RBF(Radial Basis Function)神经网络技术的分析与研究,提出了一种基于APC-III聚类算法和RLS(Recursive Least Square)算法的面向反洗钱的RBF神经网络模型并加以实现。APC-III聚类算法...针对国内外金融领域可疑交易的低检测率问题,通过对RBF(Radial Basis Function)神经网络技术的分析与研究,提出了一种基于APC-III聚类算法和RLS(Recursive Least Square)算法的面向反洗钱的RBF神经网络模型并加以实现。APC-III聚类算法用于确定RBF神经网络隐含层的中心向量,RLS算法用来调整隐含层与输出层之间的连接权值。RBF神经网络与支持向量机(SVM)和孤立点检测相比,有更高的检测率和较低的误检率,因此,提出的模型具有重要的理论和实用价值。展开更多
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.
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.
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.
文摘针对国内外金融领域可疑交易的低检测率问题,通过对RBF(Radial Basis Function)神经网络技术的分析与研究,提出了一种基于APC-III聚类算法和RLS(Recursive Least Square)算法的面向反洗钱的RBF神经网络模型并加以实现。APC-III聚类算法用于确定RBF神经网络隐含层的中心向量,RLS算法用来调整隐含层与输出层之间的连接权值。RBF神经网络与支持向量机(SVM)和孤立点检测相比,有更高的检测率和较低的误检率,因此,提出的模型具有重要的理论和实用价值。
