Please use this identifier to cite or link to this item: https://hdl.handle.net/10646/4463
Title: A conceptual framework for detecting financial crime in mobile money transactions
Authors: Gombiro, Cross
Jantjies, Mmaki
Mavetera, Nehemiah
Keywords: Mobile Money Transfer
Tax evasion
Financial inclusion
Payment systems
Money laundering
Issue Date: 2015
Publisher: Virtus Interpress
Citation: Gombiro, C., Jantjies, M. and Mavetera, N. (2015). A conceptual framework for detecting financial crime in mobile money transactions. Journal of Governance and Regulation, 4(4), 727-734. https://doi.org/10.22495/jgr_v4_i4_c6_p8
Abstract: Mobile money has made it possible for the unbanked to access financial service to areas previous not accessibly to traditional banking systems. Africa in particular, has indeed seen a growth in use of such services owing to the high penetration of mobile phones. While traditional banking services have been well regulated and secured, mobile money services are still new and vulnerable. Also, attacks and crimes targeting the internet, new technologies and new methods of payments have become sophisticated. This scenario requires novel proactive, real time techniques and solutions to detect financial crimes in mobile money transactions (MMT). The Financial Action Task Force (FATF) 2012 requires mobile money to be subject for monitoring and for compliance. Payment systems have evolved from hard cash, to credit cards, debit cards and now to the M-money, there are several approaches that have been used to detect financial crime in platforms such as credit cards and in the traditional banking system. However, most of these approaches are not suitable for m-money methods. A conceptual framework for detection of mobile money financial crime is proposed. The framework incorporates data mining techniques, big data analytics, Know Your Customers, historical databases and a knowledge base among other things.
URI: https://hdl.handle.net/10646/4463
ISSN: 2306-6784 (online)
2220-9352 (print)
Appears in Collections:Department of Computer Science

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