反洗钱监测指标数量准则构建及可疑账户识别方法研究

目前以监测可疑资金、交易报告、监管网络和记录保存为基础的反洗钱内控体系已经初步形成,但对于以洗钱为主的资金异常流动监测尚处于摸索阶段,可疑和大额交易报告也是基于人工的定性识别.随着数据挖掘和机器学习方法在各个领域的应用,通过智能数据分析判断个人和企业的金融犯罪行为已经成为一种新趋势.本文基于对洗钱监测体系中模型与方法的基础性研究,通过构建洗钱监测指标体系,并对各指标准则进行量化建模,建立起反洗钱智能监测系统的核心算法,探索构建了有效的监测指标体系和监测模型,以期提高反洗钱监测及可疑账户识别的效率和水平.

The Construction of the Quantity Standard of Anti-money Laundering Monitoring Index and the Research on Recognition Method of Suspicious Accounts

At present, the internal control system of anti-money laundering has been initially formed which is based on monitoring suspicious funds, transaction reports, regulatory networks and records. But monitoring abnormal capital flow which is the money laun- dering has still been at groping stage, and suspicious and big volume trade reports have been based on manual qualitative identification. As the application of data mining and machine learning methods to every field, using the intelligent data analysis to analyze and judge personal and corporate fmancial crime has become a new trend. Based on the fundamental research on the model and the method of money laundering monitoring system, the paper builds a money laundering monitoring index system, constructs the quantity standard of each index model, establishes the core algorithm of anti-money laundering intelligent monitoring system, explores to construct the effective monitoring index system and the monitoring model in order to improve the efficiency of anti-money laundering monitoring and identification of suspicious accounts.