Using of Machine Learning Techniques to detect Credit Card Frauds

Today is the era of digital money and the government is also promoting it to reduce corruption. People tend to use ATM cards and various credit cards for completing their transactions, but they are unaware of the fraudulent risks associated with them. A fraudulent transaction is conducted by an attacker using other's information and it causes Billions of dollars loss every year. Efficient fraud detection algorithms can be used to reduce the losses. These algorithms depend on advanced machine learning techniques, which can be helpful for fraud investigators. This paper is in two folds. First is to explore the various techniques proposed by various researchers to detect credit card frauds and second is to implement machine learning models to find frauds in credit card transactions. The aim is to identify all fraudulent transactions while reducing the number of incorrect fraud classifications. The types of credit card frauds and issues with credit card fraud detection techniques are also discussed in this paper.