부산대학교 도서관

The popularity of credit card fraud is rising as the number of cashless transactions increases. Online transactions are expanding as more people use credit cards and mobile wallets. The growth of internet commerce has also accelerated the spread of credit card fraud. Examining the cardholder's spending patterns can help identify credit card theft. Any odd behavior is grounds for the transaction to be deemed fraudulent. There are many difficulties in detection, such as frequent profile changes between fraudulent and normal transactions. Researchers use numerous techniques to detect credit card fraud, among them are hidden markov model, naives bayes classifier, decision tree, k-nearest neighbour classifier, logistic regression. The aim of this research paper is to examine divergent approaches of credit card fraud detection.