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

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.