THE USE OF DATA MINING IN DETECTING CREDIT CARD FRAUD

Abstract— Credit card fraud is a serious problem for e-commerce retailers with UK merchants reporting losses of $574.2M in 2020. As a result, effective fraud detection systems must be in place to ensure that payments are processed securely in an online environment. From the literature, the detection of credit card fraud is challenging due to dataset imbalance (genuine versus fraudulent transactions), real-time processing requirements, and the dynamic behavior of fraudsters and customers. It is proposed in this paper that the use of machine learning could be an effective solution for combating credit card fraud.According to research, machine learning techniques can play a role in overcoming the identified challenges while ensuring a high detection rate of fraudulent transactions, both directly and indirectly. Even though both supervised and unsupervised machine learning algorithms have been suggested, the flaws in both methods point to the necessity for hybrid approaches.

Prospects and challenges in the investigation of credit card fraud in Vall Region of the Gauteng Province, South Africa

Today use of Credit Card even in developing countries has become a common scenario. People use it to shop, pay bills and for online transactions. But with increase in number of Credit Card users, the cases of fraud in Credit Card have also been on rise. Credit Card related frauds cause globally a loss of billions of Rands. Credit Card fraud can be done in numerous ways. The article begins with an examination of the extent of the challenge and response by the relevant stakeholders, especially the Criminal Justice System (CJS). This study was carried out utilising a qualitative research approach with a convenience, purposive and snowball sampling techniques. Thirtynine (39) interviews were conducted to solicit the views of the participants and police investigators from Vanderbijlpark, Sebokeng, Sharpeville and Vereeniging police stations, members of the community, and victims of credit card fraud were interviewed. These interviews were analysed according to the phenomenological approach, aided with the inductive Thematic Content Analysis (TCA) to identify the participants’ responses and themes. The findings indicated that the extent of credit card fraud in Vaal region is reaching alarming rates. Based on the findings, the authors provided recommendations such as: police investigators being taken for regular workshops and training on how to investigate sophisticated methods used by perpetrators such as technology, awareness in the society about credit card fraud should be prioritised and enhanced. This study recommends that the CCTV cameras should be installed in the ATM, where cases of credit card are taking place. In addition, the police be visible in the areas which are most prevalent to credit card fraud.