Revenue Assurance Analytics Expertise

We work with Revenue Assurance professionals to identify data quality issues, fraud identification, fair usage and provide subscriber policing through metric data mining and analytics.
Revenue Assurance Analytics improves profitability, cash flow and revenues without increasing demand. This is done by ensuring fraud and subscriber fair usage and abuse of service is managed. We provide post processing solutions right up to near real time inspection using some of the most sophisticated metric based data mining technologies available today. We have teamed up with a high performance computing company to provide a powerful solutions.

In a modern telecommunication network environment there are likely to be a huge variety or charging models and complex services, serving millions of subscribers. Operating these services in the most cost effective manner introduces some unique challenges. Managing vast volumes of data to identify fraud, policing fair usage restrictions and ensuring data quality requires a huge amount of processing power and intelligent algorithms.

Our accumulated expertise with network operators, equipment vendors and strong relationships with a leading high performance computing company has allowed SMARS(R) development to directly benefit from all this related industry knowledge.

Revenue Assurance Solutions

We combine powerful metric based data mining and analytics solutions with the ultimate in deployment flexibility.

Solutions are fully scalable from a laptop right up to a high performance server. This means you can deploy a large scale enterprise solution or instantly use a portable solution provided on a laptop anywhere without the need to deploy an enterprise solution.

SMARS(R) is a complete end-to-end solution that produces fully annotated Microsoft Excel Reports, ready for easy disseminated by your colleagues and stakeholders.

There are a number of solutions listed below that provide an insight in how each adds value to your revenue assurance operation.