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
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.
