In recent days, due to the improvement in the banking system, all the payments were made through online. Among all the online transactions, the credit card transactions are in huge in number. Due to which some people are taking advantage of these and committing crimes to fulfill their needs. Credit card fraud actions are taking place continuously, which results in great economic losses. So, to avoid such frauds, banks and financial organizations are developing security-based applications. Tricky transactions are done in many ways and are divided into variant groups. Best method is selected by evaluation process using Machine Learning methods. This evaluation provides an absolute method for selecting an optimal algorithm that helps in preventing frauds based on their performance. Mainly, in this project we are concentrating on detecting real-time credit card fraud. For that, we are using predictive analysis which is implemented by Machine Learning models and API modules that helps in deciding the type of transaction that is fraud or genuine. Assessment of any strategy is accurately addressing the data distribution.
Volume 12 | Issue 2
Pages: 905-909
DOI: 10.5373/JARDCS/V12I2/S20201113