Machine Learning Approach for Credit Card fraud Detection

Abstract

Abstract: Finance fraud is a growing problem with far consequences in the financial industry and while many techniques have been discovered. Data analysis is to be applied to finance databases to automate analysis of huge volumes of complex data. Data analysis has also played a salient role in the detection of credit card fraud in online transactions. Fraud detection in credit card is a data analysis problem, It becomes challenging due to two major reasons–first, the profiles of normal and fraudulent behaviors change frequently and secondly due to reason that credit card fraud data sets are highly skewed. This project propose investigation and to check the performance of various algorithms on highly skewed credit card fraud data. Dataset of credit card transactions is sourced from European cardholders containing 284,786 transactions. These techniques are applied on the raw and preprocessed data. The performance of the techniques is evaluated based on accuracy, sensitivity, and specificity, precision.