Fraud Detection in Electric Power Distribution Networks using an Ann-Based Knowledge-Discovery Process

Nowadays the electric utilities have to handle problems with the non-technical losses caused by frauds and thefts committed by some of their consumers. In order to minimize this, some methodologies have been created to perform the detection of consumers that might be fraudsters. In this context, the use of classification techniques can improve the hit rate of the fraud detection and increase the financial income. This paper proposes the use of the knowledge-discovery in databases process based on artificial neural networks applied to the classifying process of consumers to be inspected. An experiment performed in a Brazilian electric power distribution company indicated an improvement of over 50% of the proposed approach if compared to the previous methods used by that company.