Title :
Methods and techniques to support the development of fraud detection system
Author :
Dhiya Al-Jumeily;Abir Hussain;Áine MacDermott;Gemma Seeckts;Jan Lunn
Author_Institution :
Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, L3 3AF, UK
Abstract :
The volume of fraudulent activity is increasing rapidly, with individuals and organisations being at great risk. This paper inspects the various types of fraud and the use of current systems involved in the detection of fraudulent activities across various business sectors. Through research and comparison of existing systems, this paper aims to develop a new fraud detection system which can be used by organisations, to help them detect potentially fraudulent applications. As more day-to-day tasks become feasible online, the opportunity for fraudsters has increased, therefore presenting difficulty to organisations. The proposed system is used to help determine how fraudulent an applicant is, predetermined from their previous online activity. Use of the fraud detection system can help organisations to build a case profiling their applicants, ensuring only their most trustworthy customers are granted financial facilities.
Keywords :
"Databases","Companies","Credit cards","Data mining","Data analysis","Government"
Conference_Titel :
Systems, Signals and Image Processing (IWSSIP), 2015 International Conference on
Electronic_ISBN :
2157-8702
DOI :
10.1109/IWSSIP.2015.7314217