Design and Implementation of Fraud Detection-Decision Support System Framework

The growth of digital technology with information and communication technology is on the rise. Similarly, the rise of fraudulent online payment transactions with plastic money card occurs and attracts cybercriminals because of less chance to catch, high money gain, less hard work and no physical presence. In 2021, the global economy experienced a loss of $32.34 billion due to fraudulent activities associated with plastic money card transactions. The change in technology promotes the change in transaction patterns of authorized users and fraudsters. Therefore, there is need to update the fraud detection system for fraudulent online payment transactions is very essential. The aim of the study is to identify and mitigate fraudulent online payment transactions. In order to achieve the aim of the study, the study proposes and implements a fraud detection-decision support system framework along the transaction authentication process. The idea behind the proposed framework is to compare the current and previous transaction patterns of the authorized user and generate a safe score for a current transaction. A primary dataset with 16 (transaction pattern parameters) features and 880 instances are used to assess the validity of the framework.