作　　者： ;

机构地区： 中山大学岭南学院

出　　处： 《管理与财富（学术版）》 2009年第6期169-170,共2页

摘　　要： 客户风险等级划分是反洗钱一项基础工作，由于获取客户信息的有限性，商业银行进行此项工作时面临诸多的不确定性、差异性和主观性。本文通过定义加权广义距离来表征差异性，基于最大熵原理，给出了一个客户风险等级划分方法，避免了人为因素干扰，有助于减少划分结果的不确定性和差异性，并给出具体实例加以说明。 Customer Risk Categorizing is a basis task of Anti Money Laundering（AML）. Due to the deficiency of obtaining customers＇ information, commercial banks have to face so much uncertainty, diversity and subjectivity. A customer risk categorizing method was put forward based on entropy theory and generalized distance square sum of weight, which was defined to denote diversity. It＇s found that the use of entropy theory could avoid subjectivity and reduce uncertainty and diversity of the categorizing result. At last an example was given to demonstrate the method in this paper.

关 键 词： 熵 反洗钱 风险等级划分

领　　域： [经济管理] [理学] [理学]