Abstract
Abstract: The use of credit cards has become commonplace in our daily lives, transforming the way we make cashless payments and making all types of transactions more convenient for buyers. However, credit card fraud has also become increasingly prevalent as the number of users has risen. Criminals may illegally obtain an individual's credit card information and use it for fraudulent activities. This project involved collecting a sample of a publicly available dataset from Kaggle, consisting of 284,807 credit card transactions. Extreme Gradient Boost was used to detect fraudulent transactions, and it was found to be the most effective method, achieving the highest AUC value of 97.67% after thorough analysis.
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