Main Article Content
The rapid advancement in the digital technologies has brought both positive and negative impact. So with this day by day growing technology online business and online transactions has also grown up which mostly contain transactions through credit cards, UPI and net banking.
As credit card usage increases exponentially, the chances of credit card fraud are also increasing. The credit card system is at high risk of fraud. This credit card fraud costs financial companies and consumers the most money per year.
Till date, a number of researchers have identified various methods to detect the fraud. In this paper we propose analysis of Isolate Forest and Local Outlier Factor algorithms using python and their comprehensive experimental results After the analysis of the dataset , Accuracy obtained by Local Outlier Factor is 97% and 76% by Isolation Forest.