Why CSPs now see fraud management and revenue assurance as a platform for growth
Getting urgent requests from internal users is nothing new for revenue assurance and fraud management teams in communications and digital service providers. But the nature of these requests is changing and in a fundamental way. These teams are now receiving many new requests related to growing the business, not just protecting revenue streams. For example, marketers might want to correlate margins and revenues for specific customer segments with demographic information derived from the customer relationship management system. Finance executives might want to make a similar correlation, but in reverse, so they can include segment information about customers when making decisions about margins and risk prioritization.
This is a curious trend. I mean, why are financial and marketing specialists turning to revenue assurance and fraud management systems to identify growth opportunities when these companies generally already have a data warehouse designed to help them gather business intelligence?
It turns out there are two key reasons why the data warehouse is being bypassed: Marketers and financial executives are looking for both a fast/flexible response and better data. Being an IT-controlled platform, data warehouses are constrained by the IT department’s priorities, workload, internal processes and the data sources that IT loads into the warehouse. By contrast, a revenue assurance/fraud management platform can be tuned to the needs of a small user group and is able to quickly harness new data sources.
Support for specific use cases
However, expanding the use of a revenue assurance/fraud management platform in this way requires careful planning. If you simply bolt on a generic business intelligence tool, business users then face the daunting task of figuring out what data sources, reports, dashboards, and key performance indicators to pull together.
A better approach is to simplify the analysis problem for business users by embedding intelligence into the platform. Ideally, the revenue assurance/fraud management platform should be enhanced with a new layer of software that supports specific use-case functionality. The beauty of layering is that the extensive extracting, loading, normalizing and enrichment of data required for revenue assurance/fraud management doesn‘t have to be repeated. It’s ready to immediately serve up insights around profit and margin assurance to the CFO and around usage patterns and customer preferences to marketing specialists.
Going far beyond a general purpose business intelligence tool, the analytical layer should incorporate dashboards, reports and KPIs pre-built-in to support specific use cases, meaning the business user doesn‘t have to figure out what analysis and insights he or she needs.
Let’s consider how a cross-product intelligent layer can deliver value in the LTE service area. The first step is to monitor and remedy risks. The CFO should be alerted to problems related to margins and revenue risks, which must be closely monitored since exposure is typically high for a new service like LTE.
At the same time, the fraud management platform goes to work identifying customers who are taking unfair advantage of their price plans. Once the fraud management team finds users abusing their data plan, the operator can take steps to get those customers on to alternate price plans. Rather than cut service off or limit a customer’s quality of service, the best remedy is often to offer the customer greater bandwidth if they agree to move on to a more suitable (and profitable) tariff.
Meanwhile, the revenue assurance team can analyze LTE revenue leakages and measure the profitability of specific price plans, sub services and third parties’ costs and revenues. The system should flag which LTE services have low margins and conduct a thorough segment analysis to see how customers are consuming data traffic, monitoring over-the-top app usage, and verifying bill/ settlement processes.
Delivering greater value to marketing
As they seek to drive uptake of new services, marketers are also keen to tap the data gold mine in revenue assurance/fraud management systems. Marketers are looking for easy-to-use analytical tools in a range of areas, including customer retention, the rollout of new tariffs and the sale of LTE/3G data plans. For example, marketers looking to drive uptake of LTE will want information on customers’ ARPU, profitability, usage types and content, price plan, location, handset-type and other attributes. They also need statistical models showing which customer segments have already adopted LTE, so they can identify the next segment of customers to target. An LTE dashboard, for example, should enable marketers to view customers’ usage patterns – how much data they consume per month, from which locations, what content types they use and how much money they are generating.
Ideally, the marketing analytical layer should also go one step further, calculating the next best offer/action for individual customers, including offers across shared data plans where usage is aggregated across family members.
Edited by Stefania Viscusi