BEHAVIOR MONITORING METHODS FOR TRADE-BASED MONEY LAUNDERING INTEGRATING MACRO AND MICRO PRUDENTIAL REGULATION: A CASE FROM CHINA
提出一种结合宏观与微观审慎监管的贸易洗钱监测方法，利用知识驱动的多类分类算法识别和分类监管微观实体行为，基于中国数据验证其提升金融市场管理效率的效果。
Trade-based Money Laundering, a new form of money laundering using international trade as a signboard, always appears along with speculative capital movement which has been accepted as the most concerned and consensus incentive giving rise to the collapse of the financial market. Unfortunately, preventing money laundering is very difficult since money laundering always has a plausible trade characterization. To reach this goal, supervision for regulator and financial institutions aims to effectively monitor micro entities’ behavior in financial markets. The main purpose of this paper is to establish a monitoring method including accurate recognition and classified supervision for Trade-based Money Laundering by means of knowledge-driven multi-class classification algorithms associated with macro and micro prudential regulation, such that the model can forecast the predicted class from the concerned management areas. Based on empirical data from China, we demonstrate the application and explain how the monitor method can help to improve management efficiency in the financial market.