Using Hybrid Grey Model to Achieve Revenue Assurance of Telecommunication Companies

This paper presents a hybrid intelligent system to achieve revenue assurance of telecommunication companies. The proposed system combines the grey prediction and artificial intelligence techniques to achieve a more accurate problem detector with a higher availability than those traditional audit approaches could provide. In the telecommunication companies, each revenue leakage may reach hundred millions of dollars annually. However, most practical problems in revenue assurance are very complicated and uncertain and can only be solved by human resources. A hybrid prediction model is thus introduced to tackle the problems. How to optimize the prediction model and how to measure the performance with precision and recall rates are also discussed. The paper finally exploits the empirical errors of revenue leakage as test samples to measure the prediction ability of our proposed methods and demonstrates the potential of revenue assurance for telecommunication companies.