Data Mining Application in Supporting Fraud Detection On Ethio-Mobile Services

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Addis Ababa University


The problem of Mobile frauds has been getting more and more serious for many years, and is even getting more and more worse not only in western countries but also in some developing countries. Fraud is the most significant threat to the communications business, eroding margins, consuming network capacity and jeopardizing customer relationships. Detection, Analysis and prevention mechanisms are emerging both from telecommunications operators and academia. In this paper, the possible application of data mining in supporting fraud detection on Ethio-Mobile Services has been tested by the use of neural network technique. The methodology used for this research had three basic steps. These were: data collection, data preparation, and model building and testing. The required data was collected from Ethiopian Telecommunication Corporation which is called Call Detail Record. This record shows the behavior of each mobile phone users. Next, data preparation tasks (such as data cleaning, feature selection, data transformation etc) were undel1aken. Several Neural network models were built and tested for their classification accuracy; and the model with encouraging results was taken.



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