Characterizing and preventing chargebacks in next generation web payments services

Abstract

The volume of electronic transactions has raised a lot in last years, mainly due to the popularization of ecommerce, such as online retailers. We also observe a significant increase in the number of fraud cases, resulting in billions of dollars losses each year worldwide. Therefore it is important and necessary to developed and apply techniques that can assist in fraud detection, which motivates our research. This work aims to apply and evaluate some computational intelligence techniques to identify fraud in electronic transactions, more specifically in credit card operations. In order to evaluate the techniques, we define a concept of economic efficiency and apply them in an actual dataset of the most popular Brazilian electronic payment service. Our results show good performance in fraud detection, presenting significant gains in comparison to the actual scenario of the company.