In this guest post, Adri Loloci, Senior Global Product Manager at Vodafone, discusses the issue of fraud in the mobile ecosystem and how Vodafone is combating the £600m problem using mobile network intelligence.
Fraud is a constant threat and remains a barrier to progress in the telecoms sector, costing UK consumers £600m. Thankfully, mobile network intelligence is quickly emerging as a potent solution to the fraud threat. By wielding real-time network data, new APIs and other systems, we can generate insights to enable the mobile ecosystem to fight back in earnest.
What kinds of fraud are there and how can technology take the fight to them?
The costly frauds plaguing mobile users
One of the main types of fraud are bank impersonation scams. In this scenario, someone will receive a call from someone pretending to work for their bank, telling them to move funds to a trusted account, but in fact, the money ends up with the fraudster. Anybody can be a victim of this deception. These thefts cost UK and European banks hundreds of millions of pounds, and for the individuals affected, sometimes everything they have.
Another growing threat is charge-back fraud, increasing 20% year-on-year. It’s a $20bn problem in the US. Charge-back fraud occurs when a nefarious customer makes a purchase online for a product or service with their credit card and then contacts their credit card issuer to fraudulently dispute the charge, grabbing cash back from the retailer.
We are not powerless to prevent this. Far from it. Mobile operators have extremely valuable data – data which, until recently, hasn’t been utilised to its full potential. This is network data and it can be used to understand exactly what is going on inside a network.”
How we stop them: Data-driven APIs to protect against fraud
We are not powerless to prevent this. Far from it. Mobile operators have extremely valuable data – data which, until recently, hasn’t been utilised to its full potential. This is network data and it can be used to understand exactly what is going on inside a network. This is important because it allows operators to get a vastly improved insight into fraudulent activity, and who is behind it.
An example of how data can be used to protect against fraud is the API Vodafone developed through partnering with one of the UK’s biggest banks. This API is called Scam Signal. We asked the bank to share data detailing when a particular fraud happens, in addition to relevant phone numbers, to determine if we could identify any fraudulent patterns or actors.
We then applied machine learning to those records and data points to understand the behaviour that would lead to fraud. We used these insights to develop an API that provides real-time network insights, which the bank can use to stop scams before they occur. The bank can now stop 25% more scams thanks to Scam Signal.
The road ahead
Looking further ahead, Vodafone is investigating how data and an API can be used to understand if a user has malicious purposes when making a purchase. This is critical for addressing charge-back fraud.
The next step is enabling various industries to better trust the entity behind the mobile number at a time when 15% of users on social networks are bots used to set up fake accounts. We must look at ever more effective ways to leverage data to help companies differentiate bots from users, and spot suspicious calls on a mobile network.
Fraud is evolving so the technology to tackle it must also evolve. APIs like Scam Signal empower banks and businesses to protect their customers in real-time, but this is just one solution that must be rolled across multiple territories and industries, to keep pace with the increasing breadth and sophistication of fraud. By building APIs to operate across multiple data aggregators, companies and sectors can help keep the ecosystem – and ultimately everybody – safe.
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