Voice Fraud: Understanding an Ever-Changing Threat

Operator profits are under pressure. Factors ranging from income lost to over-the-top alternatives to shifting regulatory landscapes mean that double digit margins are relegated to the past. In today’s market, all opportunities to monetise must be seized and every possible source of lost earnings prevented.

Voice fraud, in its various forms, is one of the biggest threats to operator profitability. The Communications Fraud Control Association (CFCA) estimates that 1.69% of global telecom revenue is lost annually to criminals, amounting to a staggering $38.1 billion in total, this is clearly not a minor issue that can be filed away for future attention.

Fraud is a threat to all operators, wherever they are located and whatever their size. To the more vulnerable, it could even be the difference between survival and insolvency. It certainly won’t do any good to an operator’s reputation and image to be identified as a fraud victim.

The challenge is to identify fraud as it changes and evolves. Criminals are innovative and are continually finding new ways to elude operators. While there are a range of different schemes and scenarios where fraud occurs, there are also a few common types of fraud like:

False Answer Supervision
This can either involve triggering switches to start the billing process in, favoring one interconnect wrongfully, even though end subscriber hasn’t answer the call yet. Or a call can be hijacked and transferred to an IVR system preventing the caller from reaching the intended destination and still charging the subscriber for a service he did not get.

Wangiri Fraud
The fraudster automatically robot dials thousands of mobile numbers, terminating the call after one ring. This will prompt the unaware called subscribers to call back and being lured into a premium rate number which can cost as high as 15 USD per minute.

International Revenue Share
This fraud takes advantage of international destinations where termination comes at a premium rate. Either by use of a fraudulent SIM at the originating end of the call or a colluding third party at the termination end, these high rates can be exploited.

PBX Hacking
An enterprise PBX is hacked, creating an opening for several types of fraud. A hacker might use out of office hours to make multiple calls to premium destinations, sharing the revenue with the terminating end.

Subscriber Identity Theft
In countries with high rates of incoming traffic, widely available SIMs and poor law enforcement, fraud can be committed easily by criminals using prepaid SIMs where identity is hard to trace.

Bypass Fraud
There are multiple ways for a criminal to bypass a legitimate carrier termination process, one of them would be to setup a SIM box in a destination. After publishing suspicious low rates in international LCR’s the fraudster haul voice IP traffic from legitimate wholesale carriers through the public Internet and terminate it in the destination by using local SIM cards in a SIM box.

There are different shades to each of these methods of fraud and that is what makes them so challenging to identify. The variations evolve and change over time and that is why new network intelligence and machine-learning have become so crucial in the fight against fraud.

Each type of fraud has its own characteristics that are reflected in network behaviour and can be identified with new network intelligence. A data-driven approach has been proven to work, whereby sophisticated Big Data analytics helps the service provider keep pace with evolving fraud techniques. Data captured by a Session Border Controller can both optimise performance of a network while simultaneously identifying and deterring crime.

Any loss from telecoms fraud is preventable. Tackling it leads to a healthier and more sustainable business. The constantly evolving nature of fraud makes it necessary to look at a new approach to fraud identification and mitigation, the right way is a method that evolves at a faster rate and adapts to any variation of the known methods seamlessly.

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