TY - CHAP
T1 - A Comprehensive Review of Techniques for Detecting and Preventing Card-Not-Present (CNP) Frauds
AU - Owusu-Mensah, Kwabena
AU - Yaokumah, Winfred
AU - Ansong, Edward Danso
N1 - Publisher Copyright:
© 2026, IGI Global Scientific Publishing.
PY - 2025/9/16
Y1 - 2025/9/16
N2 - This chapter reviews techniques for detecting and preventing card-not-present (CNP) fraud, which has escalated due to the rise in online transactions and the COVID-19 pandemic. It evaluates methods like machine learning, behavioral analytics and risk-scoring, highlighting their integration for effective fraud detection. Key findings indicate that traditional methods remain relevant, while advanced technologies, such as artificial intelligence, significantly enhance detection accuracy. The chapter emphasizes collaboration across sectors to combat CNP fraud and explores future research aimed at enhancing fraud detection, user experience, and ethical data usage, ultimately contributing to safer digital transactions.
AB - This chapter reviews techniques for detecting and preventing card-not-present (CNP) fraud, which has escalated due to the rise in online transactions and the COVID-19 pandemic. It evaluates methods like machine learning, behavioral analytics and risk-scoring, highlighting their integration for effective fraud detection. Key findings indicate that traditional methods remain relevant, while advanced technologies, such as artificial intelligence, significantly enhance detection accuracy. The chapter emphasizes collaboration across sectors to combat CNP fraud and explores future research aimed at enhancing fraud detection, user experience, and ethical data usage, ultimately contributing to safer digital transactions.
UR - https://www.scopus.com/pages/publications/105020840027
U2 - 10.4018/979-8-3373-0675-9.ch008
DO - 10.4018/979-8-3373-0675-9.ch008
M3 - Chapter
AN - SCOPUS:105020840027
SN - 9798337306759
SP - 283
EP - 314
BT - Innovations in Cryptocrime and Financial Fraud
PB - IGI Global
ER -