A Comprehensive Review of Techniques for Detecting and Preventing Card-Not-Present (CNP) Frauds

Kwabena Owusu-Mensah; Winfred Yaokumah; Edward Danso Ansong

doi:10.4018/979-8-3373-0675-9.ch008

A Comprehensive Review of Techniques for Detecting and Preventing Card-Not-Present (CNP) Frauds

Kwabena Owusu-Mensah
, Winfred Yaokumah
, Edward Danso Ansong

Department of Computer Science

University of Ghana

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

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.

Original language	English
Title of host publication	Innovations in Cryptocrime and Financial Fraud
Publisher	IGI Global
Pages	283-314
Number of pages	32
ISBN (Electronic)	9798337306773
ISBN (Print)	9798337306759
DOIs	https://doi.org/10.4018/979-8-3373-0675-9.ch008
Publication status	Published - 16 Sep 2025

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title = "A Comprehensive Review of Techniques for Detecting and Preventing Card-Not-Present (CNP) Frauds",

abstract = "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.",

author = "Kwabena Owusu-Mensah and Winfred Yaokumah and Ansong, \{Edward Danso\}",

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AU - Yaokumah, Winfred

AU - Ansong, Edward Danso

PY - 2025/9/16

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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.

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BT - Innovations in Cryptocrime and Financial Fraud

PB - IGI Global

ER -

A Comprehensive Review of Techniques for Detecting and Preventing Card-Not-Present (CNP) Frauds

Abstract

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