基于知识图谱并考虑智能数据关联的金融反洗钱软件设计及应用  

Anti-money Laundering Software Design and Application in Financial Field Based on Knowledge Graph and Intelligent Data Association Architecture

作　　者：王海波 WANG Hai-bo(Nanjing Cognitive Computing Information&Technology Co.Ltd.,Nanjing 210012,China)

机构地区：[1]智器云南京信息科技有限公司,江苏南京210012

出　　处：《软件导刊》2023年第1期204-209,共6页Software Guide

基　　金：江苏省双创人才计划项目(2016SCNJ007);江苏省数动未来融合创新项目(2020JSGXC02)。

摘　　要：反洗钱数据分析是提升金融行业安全性的重要技术之一。在互联网和大数据高速发展的冲击下,业内亟需形成对公客户的全维度视图,但传统反洗钱手段往往缺乏深度挖掘有价值客户信息的数据处理技术以识别和对抗风险。解决该问题的利器之一是通过搭建金融知识图谱平台,为该行业各业务部门赋能。针对此需求,设计基于知识图谱开发反洗钱软件的动因和框架,给出反洗钱软件设计关键技术,并进行软件使用案例分析与对比。应用案例表明,该软件识别率高,可为利用大数据实现反洗钱主动性预警和防控软件升级提供一定技术支持。The data analysis for anti-money laundering is one of the vital technologies for financial security.With the rapid development of the Internet and big data,it is urgent to form a full-dimensional view of corporate customers in the financial field,but traditional anti-money laundering methods lack in effective data analysis capabilities of mining the valuable customer information effectively to identify and fight against financial risks.One of the effective tools to address this problem is to build a financial knowledge graph platform,to enable better business department fusion in financial industries.To this end,describe the motivation and framework of developing the anti-money laundering software based on knowledge graph.Then,the key technologies of anti-money laundering software are presented in detail.Further,the proposed software is validated with real cases.Applications show the higher identification rate of this software,which enables big data based active earlywarning and prevention software updating for anti-money laundering.

关 键 词：知识图谱 反洗钱软件 人工智能 数据关联 

分 类 号：TP319[自动化与计算机技术—计算机软件与理论]