A Method for Identifying Financial Transaction System Fraud Using Hybrid Data Mining

Abstract

As a consequence of the exponential growth of online financial transactions and the consequent increase in the danger of fraudulent conduct, the identification of fraudulent activity has emerged as a significant concern for financial institutions. For traditional fraud detection algorithms, one of the most prevalent challenges is dealing with massive amounts of transaction data that are multi-dimensional and skewed.