Credit Card Fraud Detection

Now a days online transactions have become an important and necessary part of our lives. Credit card fraud detection is presently the most frequently occurring problem in the present world. This is due to the rise in both online transactions and ecommerce platforms. Credit card fraud generally happens when the card was stolen for any of the unauthorized purposes or even when the fraudster uses the credit card information for his use. As frequency of transactions is increasing, number of fraudulent transactions are also increasing rapidly. In order to reduce fraudulent transactions, machine learning algorithms like Naïve Bayes, Logistic Regression, and KNNetc. are discussed in this paper. The same set of algorithms are implemented and tested using an online dataset. Through comparative analysis it can be concluded that Logistic regression, naïve Bayes,and K-Nearest Neighbor (KNN) algorithms perform better in fraud detection.