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<title>Department of Computer Science</title>
<link href="https://hdl.handle.net/10646/3954" rel="alternate"/>
<subtitle/>
<id>https://hdl.handle.net/10646/3954</id>
<updated>2026-04-09T20:46:49Z</updated>
<dc:date>2026-04-09T20:46:49Z</dc:date>
<entry>
<title>A conceptual framework for detecting financial crime in mobile money transactions</title>
<link href="https://hdl.handle.net/10646/4463" rel="alternate"/>
<author>
<name>Gombiro, Cross</name>
</author>
<author>
<name>Jantjies, Mmaki</name>
</author>
<author>
<name>Mavetera, Nehemiah</name>
</author>
<id>https://hdl.handle.net/10646/4463</id>
<updated>2023-05-29T01:11:46Z</updated>
<published>2015-01-01T00:00:00Z</published>
<summary type="text">A conceptual framework for detecting financial crime in mobile money transactions
Gombiro, Cross; Jantjies, Mmaki; Mavetera, Nehemiah
Mobile money has made it possible for the unbanked to access financial service to areas previous not &#13;
accessibly to traditional banking systems. Africa in particular, has indeed seen a growth in use of such &#13;
services owing to the high penetration of mobile phones. While traditional banking services have been &#13;
well regulated and secured, mobile money services are still new and vulnerable. Also, attacks and &#13;
crimes targeting the internet, new technologies and new methods of payments have become &#13;
sophisticated. This scenario requires novel proactive, real time techniques and solutions to detect &#13;
financial crimes in mobile money transactions (MMT). The Financial Action Task Force (FATF) 2012 &#13;
requires mobile money to be subject for monitoring and for compliance. Payment systems have &#13;
evolved from hard cash, to credit cards, debit cards and now to the M-money, there are several &#13;
approaches that have been used to detect financial crime in platforms such as credit cards and in the &#13;
traditional banking system. However, most of these approaches are not suitable for m-money &#13;
methods. A conceptual framework for detection of mobile money financial crime is proposed. The &#13;
framework incorporates data mining techniques, big data analytics, Know Your Customers, historical &#13;
databases and a knowledge base among other things.
</summary>
<dc:date>2015-01-01T00:00:00Z</dc:date>
</entry>
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