基于数据挖掘的财务信息管理系统风险识别

Research on Risk Identification of Financial Information Management System Based on Data Mining

当前财务信息管理系统风险识别方法存在误差大、拒识率高等不足,为了改善财务信息管理系统风险识别效率,提高财务信息管理系统风险识别正确率,提出了数据挖掘的财务信息管理系统风险识别方法。首先对当前国内外财务信息管理系统风险识别方法进行分析,总结引起系统风险识别效果不佳的原因,然后引入数据挖掘技术对风险识别数据实施建模,刻画财务信息管理系统风险变化规律,最后与其它财务信息管理系统风险识别方法进行了对比测试。结果表明,本文方法的财务信息管理系统风险识别正确率超过95%,大幅度降低了财务信息管理系统风险的拒识率,加快了财务信息管理系统风险识别速度,具有一定的实际应用价值。

The current risk identification method of financial information management system has some shortcomings,such as large error and high rejection rate.In order to improve the efficiency of risk identification of financial information management system and improve its accuracy,a risk identification method of financial information management system based on data mining is proposed.Firstly,this paper analyzes the current risk identification methods of financial information management system at home and abroad,summarizes the reasons for the poor effect of system risk identification.Secondly,it introduces data mining to model the risk identification data,and describes the law of risk change of financial information management system.Finally,it compares with other risk identification methods of financial information management system.The results show that the correct rate of risk identification of financial information management system is more than 95%,which greatly reduces the rejection rate of risk identification of financial information management system,and speeds up the risk identification speed of financial information management system,and has certain practical application value.