Fraud identification in electricity company customers using decision tree

The objective of this work is to develop a system that pre-select electricity energy company customers who will undergo in-site inspection for frauds or faulty measurement equipments identification. The pre-selection system was built based on the electricity company database. It used attributes such as monthly energy consumption, type of consumers, previous inspection outcome, and others. A decision tree based classification system was used to reach such goal. The identification was designed, trained and tested using MATLAB code. The fraud/faulty equipments identification per number of in-site inspection rate was 40% of the total of pre-selected customers, which was above the expectation.