ملیحه وثوق - MSc. in Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
محمد تقی تقوی فرد - Assistant Prof., Allameh Tabatabaii University, Tehran, Iran.
محمود البرزی - Assistant Prof., Science and Research Branch, Islamic Azad University, Tehran, Iran.

There is no accurate data for the bank cards fraud in Iran. But, it seems to be a growing trend in this regard and in the near future it is going to become one of the critical problems in Iran's banking system. Unfortunately, not enough research works have been done in this field in our country and the banking system requires models that are efficient enough to ensure safe use of bank cards. In this paper, after identifying the most common types of bank cards frauds and fraudulent transactions simulation, Artificial Neural Network (ANN) was used for the classification of transactions into two types of legitimate (non-fraud) and fraudulent (suspicious) actions. The proposed model is a Multi-Layer Perceptron (MLP) neural network designed based on the domestic banking system and is able to classify the transactions with more than ۹۹ percent accuracy. Measures of performance calculated in this study are compared with the results of other research models. The results show that the proposed model is quite reliable and valid.

bank card, Fraud, Multi-Layer Perceptron, Neural Network