Paper Title
Bank Personnel Fraud Detection

Abstract
For building successful predictive models one should have enough number of examples for the class to be predicted (the positive class). When the number of examples of the positive class is very small, building strong predictive models becomes a very challenging task. In this study we pick up one such problem: predicting the bank personnel which might commit fraud (stealing money from customer accounts). For this problem, in order to have a strong enough predictive model, we decided to combine the powers of descriptive and predictive modeling techniques where we developed several descriptive models and used them as an input of a predictive model at the last stage. The results show that our solution approach perform quite well. Keywords - Personnel Fraud, Predictive Modeling, Banking