Electronic fraud is a problem that has become a concern for businesses of all sizes. Electronic fraud increases the loss margin as criminals go beyond brick-and-mortar enterprises to target firms with an online presence and e-payment methods. The purpose of this research is to propose a framework which decision-makers can use to anticipate threats, provide preventive measures and calculate percentage gain in income upon the implementation of the preventive measures. This proposed framework will assist in safeguarding businesses and consumers from electronic fraud on selected e-payment channels. Similarly, the framework will help minimize e-payment fraud and increase customer adoption of e-payments. The data used was obtained from the Central Bank of Nigeria. The framework’s output offers decision makers in banks and financial technology firms with historical data on the amount of e-payment fraud on each of the selected channels. The framework also allows decision-makers to forecast cyber fraud on various e-payment channels. Similarly, the framework offers methods for implementing preventive measures as well as a percentage gain in income following execution.
- Quote paper
- Olubunmi Alabi (Author), 2023, Predictive Analysis in Economic Intelligence. Case Studies of SMEs in Nigeria, Munich, GRIN Verlag, https://www.grin.com/document/1382733
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