Title of the Paper (18pt Times New Roman, Bold)

A well designed and reliable prevention system for non-payment event is very important for the telecom company. Monitoring is especially needed in case the client exceeds the level of his standard payments what can lead to his financial problems. In this paper, we propose a system describing client's behavior and informing about possible problems in advance. In this approach we apply novel ensemble methods to integrate information from many models predicting the customer's behaviour. The ensemble methods base on non-negative matrix factorization which allows identifying the fundamental prediction components. The practical experiment with prevention system confirmed that proposed procedure. Key-Words: Ensemble methods, non-negative matrix factorization, customer data modeling, prediction.