With shrinking margins in many markets, telecom providers can no longer allow 3%-15% of gross revenues to slip away through revenue leakage.
Conventional approaches to the problem generally involve plugging leaks as they are discovered, tend to be focused on specific functions (e.g., “revenue assurance built-in” billing systems), and often require some amount of manual analysis.
These methods of revenue assurance are already inefficient, unscalable and overly costly today; they’re struggling to help companies recapture revenue across the disparate legacy systems and inconsistent data sets that have resulted from years of growth through consolidation. They’ll be even less capable of handling the additional complexity being created as telecom providers expand the numbers and variety of services, bundles and partnership offerings they sell.
Analytics-driven revenue assurance is essential to ensure that companies fully realize income from their hard-won booked accounts. By incorporating analytics, you can dramatically improve financial performance in the following areas:
Detect leakages and causes across complex operational processes
Much of the leakage is happening in the handoff between functional areas, which is why it’s not being caught.
Conventional revenue assurance solutions, for example, rely on the switch billable call detail record (CDR) for detection. Yet revenue leaks may frequently be the result of errors or manipulation that cause “answer/no charge” transactions. In this case, the switch never generates a CDR at all.
In addition, poor quality data in the switch-generated record can cause problems later in mediation, rating or billing. If the provider is using a billing system with “revenue assurance built in” it may be able to detect rating discrepancies. However, because it doesn’t understand anything about mediation or switch processes, it can’t determine the actual cause of the problem.
Best-in-class revenue assurance solutions analyze what is happening across the network so they can not only detect these complex leakages, they can also reveal the cause. For example, the system might detect a leak associated with a particular rate plan for customers who’ve activated in the past 20 days—and point analysts to a missing rate plan or misapplied rate within a plan.
Find unknown problems
Some companies try to rely on rules-driven detection to stop revenue loss. The detection power of such systems is limited to leaks the analysts writing the rules know about and what they believe is going on in the network.
More advanced systems, which incorporate both rules and analytics, detect problems telecom companies don’t even know they have. By analyzing thousands of predictive variables innumerable times, the analytics learn about normal patterns of networked processes.
They’re able to detect leaks based not only on known patterns, but pattern variations and even anomalies indicated by the absence of patterns—essential to helping telecom providers minimize problems as their networks and service mixes grow and change.
Fair Isaac is using an Automatic Identity Identification statistical model that computes commonalities across risky transactions/accounts to provide additional insight into the possible macro causes for abnormality.
For example, 8,000 mobile phones may be flagged for revenue assurance issues. The Automatic Identity Identification model will compute commonalities across these cases and potentially determine that 90% are associated with a particular international switch or that a particular MMS download is not properly being billed.
Prioritize response based on loss potential
Analytics-based detection ranks potential leaks based on incident rate and potential losses, enabling telecom companies to address the most costly problems first. Because the models know how much money has been lost by leaks associated with certain patterns and pieces of patterns, they direct particular scrutiny to expensive services, such as international calling, wireless premium services and content purchases.
Predict and prevent future leaks
The best systems go beyond detecting current links to predicting where future leaks may occur, enabling telecom providers to prevent losses. Advanced systems are able to make these predictions because they’ve learned, by analyzing past leakages, to spot the very earliest signs. They can also generalize learned principles and apply them to new situations.
By combining the power of analytics and automation and applying them to operational decision making, telecom providers can dramatically improve profitability. By connecting decisioning, so that data-driven insights and operational results in one area support and inform processes in other areas, they can achieve even higher levels of financial performance.
This is an excerpt from the white paper “Predictably Higher Financial Performance: Using analytics and automation to improve results by double digits across the telecom customer lifecycle.” Click here to download.