An evaluation of card fraud detection techniques in the banking sector: A case of NMB bank MSASA.

Author
Ruth Jokonya
Title
An evaluation of card fraud detection techniques in the banking sector: A case of NMB bank MSASA.
Abstract
With the increasing prevalence of card fraud in the banking sector, it has become critical for banks to employ effective techniques for preventing and detecting card fraud. This research paper aims to evaluate different card fraud detection techniques employed in the banking sector, focusing on NMB bank as a case study. The study objectives are to identify the various card fraud detection techniques, assess their effectiveness, identify weaknesses, and make strategic recommendations for improving their effectiveness. The literature review reveals the different card fraud detection techniques used in the banking sector, including machine learning algorithms, purchase behaviour analysis, and Two-factor authentication. These techniques are effective in detecting fraudulent activities when implemented correctly, but one significant weakness is their susceptibility to false positives. Banks need to address this challenge and the rapid evolution of fraud technologies by upgrading fraud detection systems, improving data quality and management practices, enabling cross-organizational information sharing, and customer education and security awareness programs. The study found that the various card fraud detection techniques currently in use at NMB bank are very effective in detecting instances of card fraud. Nonetheless, these techniques are not immune to weaknesses, particularly vulnerability to false positives. Therefore, banks need to implement strategic recommendations to improve the effectiveness of their card fraud detection techniques. Overall, this research paper provides guidance to banks on how to tackle the issue of card fraud effectively.
Date
2023
Publisher
BUSE
Keywords
Card Fraud
Banks
Supervisor
N/A
Item sets
Department of Intelligence and Security Studies
Media
JOKONYA RUTH.pdf

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