基于改进随机森林的洗钱交易角色识别应用  

Role Identification of Money Laundering Based on Improved Random Forest

作　　者：张昊 黄蔚[1] 胡国超[1] 

机构地区：[1]华北计算技术研究所,北京100083

出　　处：《计算机与现代化》2018年第2期101-106,共6页Computer and Modernization

摘　　要：对于识别洗钱交易中钱庄账户的方法、现有公安办案方法与现有研究基于机器预警方法存在准确度低且滞后的问题,本文分析洗钱犯罪集团中钱庄与客户的交易行为特点,从主体背景属性、交易统计量、交易网络、交易行为离群4种角度提取一系列特征进行刻画,并通过随机森林进行特征选择与优化,在已经标注过的数据上进行模型训练与验证,形成一个能够对参与洗钱交易者身份进行自动识别的应用。通过实际数据验证可以发现有严重危害的钱庄经营者。Aiming at the problems of low accuracy and delay of the method of identifying the bank account in the money laundering transaction,the method of public security unit handling,and the existing research based on machine warning,this paper analyzes the trading behavior characteristics of the bank and the clients in the money-laundering crime group,extracting a series of features like the personal background attributes,trade statistics,trading platform,trading behavior to depict outliers from four kinds of view. The features are selected and optimized by random forest model. The annotated data is trained and verified. An application is formed for automatic recognition of traders involved in money laundering. Through the actual data validation,those banking operators with serious hazards can be found out.

关 键 词：洗钱交易 角色识别 交易网络 中心性 决策树权重 随机森林 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]