Detecting defaulters for consumed electric energy with neural network clustering

There are two main fields in the business activity of electric power industry: electric energy distribution and its collection. The first field includes the building and maintenance of electric power facilities according to the needs of consumers with the appropriate strategy of electric energy distribution in the situations of extremely poor and brisk demand. The second field, electric energy collection exerts influence on liquidity and business performance. This second field, electric energy collection, has priority in electric power industry, and it is quite understandable. The work deals with the application of neural network clustering analysis for detecting defaulters for consumed electric energy in the territory of the City of Subotica in the period of 2001 to 2006. The results of applying this data mining technique are precious for the Subotica electric power distribution enterprise because in this way a campaign can timely begin for regular payment of electric energy for those consumers being late to pay in the last five years.