Fraud detection in credit card transaction using face recognition techniques

Abstract

Credit cards are widely used around the world. People, who have the ability to buy anything they need with a price tag on the item, have many different ways to make payments such as online transactions, credit card transactions and monthly installments. Using credit and debit cards is becoming the most common payment method among a large number of buyers. In the credit card transaction, access is granted if one has a credit card and passes a verification. Such an approach poses several threats: unauthorized possession of credit cards (stolen or borrowed), clone card risk, etc. Credit card users face a number of privacy issues. This is most common when users give away their credit cards to unfamiliar people or lose their cards. One solution to minimize these threats is to verify the bio-metric relationship between the credit card holder's signed face image and the user's face image captured by a camera when using the card. The main objective of this research is to develop a software to reduce fraud transactions occurring through credit card payments using artificial intelligence to detect faces from a camera. This paper proposes a method for credit card transactions that combines face detection and face recognition technology.