Application of Classification Models on Credit Card Fraud Detection
Aihua Shen, Rencheng Tong, Yaochen Deng · 2007
Along with the great increase in credit card transactions, credit card fraud has become increasingly rampant in recent years. This study investigates the efficacy of applying classification models to credit card fraud detection problems. Three different classification methods, i.e. decision tree, neural networks and logistic regression are tested for their applicability in fraud detections. This paper provides a useful framework to choose the best model to recognize the credit card fraud risk.