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Detection of Anomalous Transactions in Mobile Payment Systems

Detection of Anomalous Transactions in Mobile Payment Systems

Ibrar Hussain, Muhammad Asif
Copyright: © 2020 |Volume: 1 |Issue: 2 |Pages: 9
ISSN: 2644-1705|EISSN: 2644-1713|EISBN13: 9781799804642|DOI: 10.4018/IJDA.2020070105
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MLA

Hussain, Ibrar, and Muhammad Asif. "Detection of Anomalous Transactions in Mobile Payment Systems." IJDA vol.1, no.2 2020: pp.58-66. http://doi.org/10.4018/IJDA.2020070105

APA

Hussain, I. & Asif, M. (2020). Detection of Anomalous Transactions in Mobile Payment Systems. International Journal of Data Analytics (IJDA), 1(2), 58-66. http://doi.org/10.4018/IJDA.2020070105

Chicago

Hussain, Ibrar, and Muhammad Asif. "Detection of Anomalous Transactions in Mobile Payment Systems," International Journal of Data Analytics (IJDA) 1, no.2: 58-66. http://doi.org/10.4018/IJDA.2020070105

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Abstract

Mobile payment systems are providing an opportunity for smartphone users for transferring money to each other with ease. This simple way of transferring through mobile payment systems has great potential for economic activity. However, fraudulent transactions may occur and can have a substantial impact on the economy of a country. Financial fraud and anomalous transactions can cause a loss of billions of dollars annually. Therefore, there is a need to detect anomalous transactions through mobile payment systems to prevent financial fraud. For this research study, a synthetic dataset is generated by using a PAYSIM simulator due to the lack of availability of a realistic dataset. This research study performed experiments on a financial transactional dataset using eight data mining classification algorithms. The performance of classification models was measured by using evaluation metrics: accuracy, precision, F-score, recall, and specificity. A comparative analysis of classification models was also performed based on their performance.

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