可视化数据挖掘在信贷欺诈检测中的应用

Application of Visual Data Mining to the Study on Fraud Detection in Fiduciary Loan

检测和防止信贷欺诈行为对于规范和维护合理的金融秩序具有重要意义。对于银行中的信贷行为,应用异常检测和人工神经网络等数据挖掘方法,检测和分析其中可能存在的欺诈行为;借助于Clementine软件对信贷数据进行提取与处理,实现了数据挖掘过程的可视化。应用实例表明,该方法直观并且有效。

In order to standardize and safeguard the financial order,it is important to detect and deter fraud behavior in fiduciary loan.This paper makes a study on fraud detection in fiduciary loan.Firstly,Data mining methods anomaly detection and artificial neural networks are used to detect and analyze the possible fraud behaviors in bank fiduciary loan.Furthermore,with the help of data mining software SPSS Clementine,the loan data is extracted and processed,and the visual process of data mining is implemented.Finally,the practical application shows that this approach is visualize and effective.