Credit Card Fraud Detection; A Machine Learning Approach
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Date
2020-11
Authors
Glah, J.
Journal Title
Journal ISSN
Volume Title
Publisher
University Of Ghana
Abstract
In recent times, credit card usage has increased tremendously because it is convenient
to use and also saves a lot of time. Credit cards are rectangular plastic cards
issued by banks which allow a person to borrow funds from a pre - approved limit
to pay for one’s purchases now and pay later. In the same manner, credit card
frauds have also been on the increase causing huge sums of financial loss to credit
card issuers. Credit card fraud is the use of a credit card by someone who is not
the owner of the card and is not allowed to use it. In this study, three classification
methods were used to do a deep analysis of credit card transactions history and the
fraud detection models built. This study presents and demonstrates the advantages
of support vector machine, artificial neural network and the k - nearest neighbor
algorithms to the credit cards data for the purpose of reducing the bank’s losses.
The results show that the linear support vector machine and k - nearest neighbor
approaches outperform artificial neural network in solving the problem under investigation.
This study allows for multiple algorithms to be integrated together as
modules and their results combined to increase the accuracy of the final results.
Description
MPhil. Statistics
Keywords
Credit Card, Fraud, Learning