Using the rough set theory to detect fraud committed by electricity customers

• In this paper rough set theory application for electricity fraud detection is given.
• Point of paper is indicator’s estimation of suspicious customers in boundary region.
• Theoretical foundation is balance of total, invoiced and non-technical losses energy.
• The proposed method can be applied for sufficient number of relevant attributes.
• Discretization of continuous attributes with equal frequencies is used.

High values of total percentage losses of electricity in Serbia’s distribution network and a very small percentage of success in detecting electricity fraud indicate a need for a sophisticated means of detecting fraud perpetrators. In order for this task to be performed efficiently, the authors of the paper emphasize the need for a suitable and comprehensive use of the billing system or the database of the amounts of invoiced spent electricity in accounting periods and other relevant data regarding registered customers. For that purpose, they suggest using the rough set theory and give a general approach to its use. The point of the paper is forming a criterion for the estimation of accurate (suitable) discretization of original data. The criterion is based on the amount of lost not invoiced electricity due to electricity fraud. Based on consumption characteristics of detected fraud of customers whose measurement points were regularly (monthly) read, a list of the suspicious customers will be formed which will serve as the basis for sending expert teams to specified locations with the task to confirm or dismiss the fraud suspicion.