Abstract: Credit card has an important role in our day- to-day lives. It is now being widely used all over the world for transactions, irrespective of the geographical boundaries People use credit card for their purchase, it allows them to pay it later. Credit card fraud happens when someone steals the information or loses the card. Criminals may be using technologies such as Trojan or Phishing to get card details. Therefore, an effective fraud detection method is important since it can identify a fraud in time when a criminal uses a stolen card to consume. One method is to make full use of the historical transaction data including normal transactions and fraud ones to obtain normal/fraud behavior features based on machine learning techniques, and then utilize these features to check if a transaction is fraud or not. In this paper, Machine Learning algorithm is used to train the behavior features of normal and abnormal transactions. We implement this using Random forest machine learning algorithm in OpenCV and analyze the performance on credit fraud detection.

Keywords: Credit card fraud, Machine learning, Random Forest, openCV

PDF | DOI: 10.17148/IJARCCE.2021.10320

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