Risks and Barriers Associated with Mobile Money Transactions in Tanzania

Abstract

The study was about Risks and Barriers Associated with Mobile Money Transactions in Tanzania. The focal point of the study was to spot and reveal risks and barriers experienced by mobile money users in mobile money transactions (MMT) and the frequencies of their incidences. It also assesses the level of users' understanding and how they can avoid themselves from barriers and risks exposing environment. The research was based on primary data which was collected in a survey done in Ilala district through questionnaires. Data analysis was based on descriptive statistics and interpretation based on positivist assumptions in which the results were quantitative and independent from the researcher. The research findings reveal that while the most likely experienced risks are a loss of password, fake transaction request, and fake money, the barriers are a poor network, agent lack liquidity, and lack of identity card. However, the rate of incidence of risks and barriers in MMT are moderates. The study, therefore, recommend that the regulatory authority should guarantee the security of mobile money users by improving MMT rules and regulations, they should also stress mobile companies to create MMT awareness in risks, rules and regulations to mobile money users to encourage their participation in this industry and finally the mobile company should improve mobile money network infrastructures and application platforms.

eKichabi v2: Designing and Scaling a Dual-Platform Agricultural Technology in Rural Tanzania

“…Aker et al [4] review various attempts to use agricultural ICTs in Africa and offer sociological and anthropological insight into how these platforms alter the relationship between the provision of information and trust. For rural communities in Tanzania, trust takes different forms [7,51,79]. Our work documents localized ways to confer trust through design that we learned through iterative user testing.…”

Development of a secure multi-factor authentication algorithm for mobile money applications

“…Ali et al (2020b) (Aloul et al, 2009;Rodrigues et al, 2016;. Brute-force attacks on mobile money are simple and have a high success rate because of the simplicity of the PINs (Mtaho, 2015;Raphael, 2016;Castle et al, 2016;Reaves et al, 2017;Ali et al, 2020a). In addition, mobile money agents and customers who use smartphones to carry out mobile money transactions have a high chance of their mobile money PINs being compromised because their hands leave a greasy residue and scratch on the smartphone's touchscreen that attackers can use to guess their mobile money PINs easily (Kunda & Chishimba, 2018).…”

“…The adversaries can also disguise themselves as legitimate mobile money agents or customers to control and access mobile money systems and their services (Ali et al, 2020a). Mobile money subscribers have the habit of sharing their mobile money PINs among friends and family members, thus, making it easy for attackers to perform illegal transactions and even update the victims' PINs (Mtaho, 2015;Raphael, 2016;Buku & Mazer, 2017;Lonie, 2017;Das et al, 2018;Ali et al, 2020a;Ali et al, 2020b). Attackers use social engineering to lure mobile money agents and customers into revealing their confidential information.…”

“…A guessing attack is where attackers hunch the mobile money subscribers' PINs during the authentication (Ali et al, 2020a). Most mobile money schemes use PINs of four or five digits as one of the authentication factors, and these PINs are unmasked during their entry, thus making them guessable (Mtaho, 2015;Raphael, 2016;Reaves et al, 2017;Bani-Hani et al, 2019).…”

“…At the same time, a distributed DoS attack is where the fake traffic that overwhelms the mobile money servers and bank servers come from various distributed sources, which is hard to stop (Ali et al, 2020a;Ahmed et al, 2021). The main aim of DoS and DDoS attacks is to cause the servers to crash and deny legitimate subscribers' real-time access to the mobile money systems, services, or networks, which causes the subscribers, mobile money service providers, and banks to lose money (Mutong'Wa & Khaemba, 2014;Raphael, 2016;Castle et al, 2016;Bosamia, 2017).…”