The effect of feature selection on credit card fraud detection success Özellik seçiminin kredi karti sahtekarliǧi tespiti başarisina etkisi

Bayhan E., YAVUZ A., GÜVENSAN M. A., KARSLIGİL YAVUZ M. E.

29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021, Virtual, Istanbul, Turkey, 9 - 11 June 2021 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu53274.2021.9477812
  • City: Virtual, Istanbul
  • Country: Turkey
  • Keywords: credit card fraud detection, autoencoders, feature selection, ENSEMBLE
  • Yıldız Technical University Affiliated: Yes

Abstract

© 2021 IEEE.In this study, a deep learning based credit card fraud detection system has been designed and implemented. The information provided by credit card transactions is not sufficient in fraud detection systems. In order to increase the success of the model, new features were created by grouping the previous transactions according to features such as merchant category, transaction type, and payment type. Then these features were selected with feature selection methods and the most impact ones were determined. Thus, thanks to the newly added features, the payment habits of the cardholder were better learned by the model and the success of the model was increased.