CSPs want subscribers to be using their services as often as possible. But treating high usage as good thing would be a huge mistake.
You’re on holiday relaxing on the beach trying to avoid your phone. You’re not responding to work emails but when you hear a beep you begin to worry. “Is my neighbour having a problem feeding my cat? Did my mum fall down the stairs? ” Before you know it you’re already looking up the results for your favourite football team, reading Wikipedia to learn about the history of Papa New Guinea and watching far too many videos on YouTube. The experience might not be exactly the same for you, but the lesson is universal. High usage can be a pain but it’s often accidental. This should in theory result in more money for an operator. So is it actually a problem?
High usage is not in itself a type of fraud, so most fraud teams aren’t necessarily monitoring it. Superficially communications service providers (CSPs) want subscribers to be using their services as often as possible, so some operators still don’t control it from a customer service angle either.
How to Make High Usage Work for You
From a customer service viewpoint, monitoring high usage means CSPs can alert people to potential bill shocks. If you could see anomalous data usage then you might be able to send subscribers a message to remind them they haven’t turned their Spotify to offline mode for example. By doing so, the amount of negative news stories which harm your company’s reputation should decline and your existing subscribers will be much happier with their service.
A sales team could benefit too, as having access to this data allows them to up-sell other kinds of services. Seeing a subscriber with a high usage of SMS messages to Kenya? Offer them a special international messaging plan!
The biggest gain to be made though comes from a fraud perspective. As mentioned, high usage in itself can’t be considered a fraudulent activity. Although there might be payment and collection problems as a result from unintentional high usage, it’s not malicious and it’s not organised. To most, it’s just an accidental by-product of inattention to circumstance. However, as we see with subscription fraud, a smart fraud analyst can take this opportunity to discover and prevent other kinds of fraud before they happen.
Whether we’re considering the potential to exploit network weakness to perpetrate roaming fraud, IRSF, bypass or a significant amount of other fraud types, a common indicator between them all is abnormal usage behaviour. If we follow this train of thought to its logical conclusion, by being able to accurately and timely detect high usage patterns, CSPs will be able to effectively predict and prevent future fraud as well as remove “false positives” (legitimately accidental high usage events from otherwise profitable subscribers). This can only improve the bottom line and make life easier.
Where to Look
When it comes to measuring high usage activities, there are 4 key areas to look at which incorporate calls, messages and data.
1) On-Net Usage
You will need to be able to check the activities and audit the CDRs of calls and messages between subscribers on your network. High values outside the norm here could be indicators of potential prepaid fraud for example.
2) Off-Net Usage
You’ll also need to be able to check the same information for traffic heading towards your competitors. Bypass fraud can be a problem when CDRs are generated across networks, so this can be a useful metric to track.
3) International Usage
By tracking the traffic generated to international numbers you’ll be at a great advantage. The potential for bill shocks and upselling is huge, but more importantly these are the exact kind of scenarios that allow IRSF to flourish, which is a huge and persistent problem for all operators.
4) Visitors Usage
Roamer In usage could be a valuable indicator of roaming fraud. It’s essential that this is monitored too.
Improving Customer Satisfaction and Decreasing Fraud Loss
As long as you have a system which can check the CDRs generated at network switches in near-real time then you’ll be well placed to analyze these behaviors and take appropriate action. In the end you’ll be looking at reduced fraud losses, happier customers and more revenues.
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(*) Photo by pixabay.com from Pexels
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