Credit card fraud detection system using machine learning technique
Ayushi Maurya, Arun Kumar
Abstract
Over the years, with the development of e-commerce, people are mostly making online transactions, and the risk of getting scammed has also increased. This in turn forces the financial institutions to improve continuously and upgrade their model. Machine Learning techniques were used to detect fraud in credit card transactions, but working with real-time data can be tough for machine learning to handle. Thus, implementation of blockchain techniques with machine learning to improve the efficiency and accuracy of the model. In the proposed model, Ethereum dataset has been used to check the fraudulent transaction and secure it with the help of machine learning algorithms. Out of all the classifiers XGBoost has attained the highest accuracy of 99.21% for the stated dataset.