Artificial immune system for fraud detection

Credit card transactions continue to grow in number with the rapid growth of the electronic commerce, leading to a higher rate of stolen account numbers and subsequent losses by banks. Improved fraud detection thus has become essential to maintain the viability of the payment system. In this paper, we propose a case-based genetic artificial immune system for fraud detection (AISFD). It is a self-adapted system designed for credit card fraud detection. With the case-based learning model and genetic algorithm, the system can perform online learning with limited time and cost, and update the capability of fraud detection in the rapid growth of transactions and commerce activities.