Abstract:
Credit card fraud is becoming increasingly widespread as more of us use credit cards for payment. This is owing to technological advancements and a surge in online transactions, which has resulted in scams incurring massive financial losses. Every year, credit card firms and banks lose billions of dollars to such fraudulent actions, costing them a significant portion of their revenue and affecting the jobs of several people. As a result, we must examine and distinguish between fraudulent and nonfraudulent transactions. This article focuses on identifying fraud detection. This research proposes a Deep Learning model ANN Artificial Neural Network for monitoring and detecting fraudulent activity. The proposed method is capable to detect fraud transactions with an average accuracy of 97 percent and F1-Score of 0.97 of both 0 and 1 cases.
