基于逻辑回归的企业大额可疑外汇资金交易识别模型  

Identifying Model of Large Amount of Enterprises' Suspicious Transactions of Foreign Exchange Based on Logistic Regression

作　　者：孙景[1] 李志伟[1] 刘炜[2] 

机构地区：[1]西安交通大学经济与金融学院,陕西西安710061 [2]广东发展银行科技部,广东广州510080

出　　处：《上海金融》2008年第6期58-61,共4页Shanghai Finance

基　　金：国家自然科学基金项目《基于数据挖掘的可疑金融交易识别研究》,项目编号70771087

摘　　要：本文根据逻辑回归原理与数据挖掘技术,建立了企业大额可疑外汇资金交易识别模型,用于分析银行企业客户洗钱的概率及洗钱事件发生的可能性。本文的目的是通过对具有洗钱嫌疑的银行企业客户进行识别和预测,为银行反洗钱技术提供参考。Using logistic regression theory and data mining technology, the paper builds an identifying model of large amount of enterprises＇ suspicious transactions of foreign exchange to analyze the probability of money laundering in banks＇ enterprise clients. The purpose of the paper is to help banks with anti-money laundering technology by identifying and forecasting banks＇ suspicious enterprise clients.

关 键 词：反洗钱 可疑金融交易 数据挖掘 逻辑回归 

分 类 号：F830.92[经济管理—金融学]