Credit Card Fraud Prevention Planning using Fuzzy Cognitive Maps and Simulation

For any financial organization, development and management of fraud prevention plan is a complex yet crucial process. Most of the organizations opt for fraud detection and prevention plans to sustain their marketplace. With the advancement of technology and diversification in user's demand for high security and privacy, it is important to improve fraud prevention planning for financial organizations and banks. Different processes like fraud detection, fraud risk assessment, fraud perception, monitoring and control are involved in fraud prevention planning. It is difficult for Chief Investigating Officer (CIO) to grasp the dependencies among all processes. Similarly, the effect of inefficiencies may raise severe concerns to the planning model and organization as well. This paper considers the formulation of fraud prevention plan for credit cards through implementation of Fuzzy Cognitive Maps (FCM). Furthermore, our aim is to represent the complexity of relationships that exists in different processes of fraud prevention model. The model has been validated through mathematical simulation using log sigmoid function and then risk prediction has been done on single what-if scenario. The contribution of this paper is to analyse and predict risks related to fraud prevention planning in credit cards and help in better decision making.