At Neural Technologies, we’ve got a long history of working to support communication service providers (CSPs) in tackling scam calls and fraud in order to reduce revenue leakage. The reality for customers, however, is that the cost of fraud is more than just a top-line summary of revenue protection, it’s a very personal problem for many citizens in markets around the world. The Risk & Assurance Group (RAG) RAFM Survey 2020 estimates fraud costs customers of CSPs USD48bil annually. That’s a remarkable figure in itself, but billions lost across the globe can sometimes hide the deeply shocking personal stories of individual loss.
The personal effects of fraud and scam calls
Preventing a single scam call can save your business a minimal amount of lost revenue, but it could be the barrier between a customer losing their life savings. The sophistication of fraudsters is increasing, and now includes a suite of potential scam call techniques such as wangiri fraud, CLI spoofing, swim swap fraud, as well as more complex cases such as identity theft.
One case from the UK in 2018 gained national news attention when a 46-year-old woman was scammed out of GBP40,000 (~USD55,000) through a call spoofing scam. Fraudsters made a scam call by spoofing the phone number of the victim’s bank, leading her to believe it was an official call to alert her to fraud. Reassured by the seemingly official correspondence number, the victim was tricked into transferring away her life savings. This shows the very personal cost of call spoofing fraud.
Caller ID spoofing fraud can also form part of a wider scam attempt, often leading to major financial losses for victims. A report in the UK newspaper The Guardian in December 2020 revealed the case of one victim who lost over GBP100,000 (~USD140,000) and was at one point rendered homeless by the cost of such fraud. Call spoofing and scam calls can be used to gain insight and leverage on victims, who are then targeted through more sophisticated and ongoing scams.
Scam texts can also be a major area of fraud risk, often leveraging sim swap fraud to target customers. In one case from Australia in 2019, a family lost AUD17,000 (~USD13,000) to fraudsters through a sim swap fraud after receiving a text purporting to be from their bank. The text targeted the family, urging them to click a link due to a problem with the account. Having then provided key personal details on the linked page, the victims found their mobile number quickly changed, and money transferred out of their account before they could prevent it. Fraudsters had used those details in order to gain access to the account to drain the funds from the bank.
These cases are sadly not unique, with scammers often using sim swap techniques to fraudulently breach two-factor authentication protections on banks and financial transactions. A case in San Francisco, USA, saw a man lose USD1mil in investments due to this sim swap scam. Fraudsters manipulated processes in the CSP to swap out the victim’s sim and gain control of his phone number, giving them access to authentication messages for password resets in everything from social media to banking. Fraudsters then simply took control of the victim’s accounts and transferred out the victim’s life savings.
Tackling fraud means preventing customer losses
CSPs have a responsibility to tackle fraud not only to eliminate operational losses for their business, but also to prevent the very real personal effects of fraud, and the long-lasting financial impacts such acts can have on customers.
At Neural Technologies we want to partner with CSPs to tackle this challenge, with advanced machine learning and artificial intelligence solutions that deliver effective fraud management for service providers.
Fraud is a huge market challenge for CSPs across the world, costing customers and businesses USD92bil annually. That reflects a huge opportunity to prevent revenue leakage for CSPs, while protecting the essential financial security of billions of individual customers.
The original version of this article was published on the Neural Technologies blog. It has been reproduced with their permission.