An Overview of Credit Card Fraud Detection Learning Techniques

EasyChair Preprint 11527

Abstract

Credit card fraudsters are becoming more creative, altering their behaviors, and finding
new ways to trick computer systems. Card fraud has become a major national and global
threat to e-commerce causing losses of great amounts of money. Immediate attention needs
to be directed towards improving existing techniques, or creating new methods for
pinpointing fraudulent transactions. Supervised classification algorithms have proven to be
accurate measures for predicting illegal transaction with more than 90% accuracy. This
work reviews existing techniques and compares their reliability by examining their
accuracy and speed on their application to three deferent data sets.

Keyphrases: Supervised Learning Techniques, Types OF Fraud, credit card fraud

@booklet{EasyChair:11527,
  author    = {Norah Aljalawi},
  title     = {An Overview of Credit Card Fraud Detection Learning Techniques},
  howpublished = {EasyChair Preprint 11527},
  year      = {EasyChair, 2023}}