Authorised Push Payment (APP) fraud is the UK’s fastest-growing source of direct consumer losses, with over £257.5 million lost in the first half of 2025, a 12% increase on the same time last year. Significantly, while the majority of APP fraud cases began on online platforms, 17% also originated on telecommunications platforms.
We sat down with Henry Howe, Head of Product in our Mobile Intelligence unit, to examine how these scams spread and why traditional fraud systems simply aren’t fast enough to stop them. He also discussed how JT’s live mobile data can help banks identify and block suspicious payments before they’re processed.
Unlike crude phishing emails in the early days of internet banking, APP scams are much more calculated. They seem legitimate — even to digitally literate consumers — because they’re based on real details harvested from exposed social media accounts or past breaches.
As Henry explains, “The root cause of a lot of this is social engineering. Everyone is now online in some shape or form.”
The more consumers rely on digital services, the more data cybercriminals can harvest and abuse. Large fraud rings can now very easily scan and collect the personal information they need to convincingly impersonate figures of authority and coerce victims into transferring funds.
Consumers can’t be expected to recognise every threat by themselves. New laws are holding banks increasingly accountable for fraud losses, pressuring the financial sector to systematically stop deceptive payment requests.
Unsurprisingly, fraudsters go straight to where most people manage their money: the mobile phone. Scammers might take control of a victim’s number through a SIM swap and intercept two-factor authentication codes. Or, they might spoof a bank’s caller ID and force the victim to approve a payment.
Mobile phones are also used in one of the most profitable forms of APP fraud: conveyancing scams. Criminals pose as solicitors and trick homebuyers into transferring large amounts into fraudulent accounts — sometimes exceeding £250,000, wiping out savings that had taken years to build.
Fortunately, these scams don’t have to go undetected. They often leave mobile traces before the money moves.
Using mobile network signals to log account- and device-level anomalies in real time — such as whether a SIM card was recently swapped or a device suddenly changed — can help banks pre-empt account takeover or impersonation attempts. These mobile-layer signals flag suspicious behaviour as a transaction is being initiated, giving analysts a window to intervene.
JT’s Scam Signal gives financial institutions a real-time snapshot of mobile-based risk at the moment of transaction.
Let’s say a customer is about to transfer funds. Before the bank processes that payment, financial institutions can access a wealth of real-time information from mobile operators via the JT Mobile Intelligence APIs.
If the signal points to something suspicious, the bank can block the payment and call the customer or ask for in-app confirmation
This stops the transaction before money is transferred — and spares the bank the cost and complexity of recovering stolen funds or refunding victims after the fact
Henry calls Scam Signal “the next evolution” of JT’s mobile intelligence services.
It builds on SIM swap detection by pulling in additional mobile network signals linked to impersonation attempts and other scam tactics, giving banks more context at the moment of transaction.
Now more than a year into deployment, Scam Signal is already integrated with several UK banks and their fraud partners.
JT has been building relationships with operators, industry bodies like UK Finance and the GSMA, and technology partners like FICO to turn mobile network data into live fraud signals banks can trust. That ecosystem makes the data credible and actionable, because fraud prevention only works if the data is accurate, timely, and fully consented.
JT’s privacy-first framework ensures that every data point is approved by the mobile operator and used with the customer’s permission. And with FICO, JT has embedded Scam Signal directly into fraud models used by major UK banks.
Across deployments so far, JT’s mobile intelligence data has helped partners achieve:
With JT’s Scam Signal, fewer cases escalate to reimbursement — and more importantly, fewer victims lose their hard-earned savings.
JT is already expanding Scam Signal with new data attributes from mobile operators, offering even deeper insight into customer risk and behaviour.
Henry explains that Scam Signal’s roadmap includes increasing market coverage and refining existing signals. “We have a handful of other data attributes which we want to include over the course of the coming months.”
JT is also working hand-in-hand with clients and partners to monitor how threats mutate as fraud rings adjust to countermeasures.
Fraud models need to give banks the context they need to stop high-risk transactions before they go through. That means integrating live mobile intelligence signals into fraud decisioning and using only carrier-verified data sources that are legally approved for real-time risk screening.
JT’s Mobile Intelligence platform turns live mobile data into fraud signals banks can use to stop high-stakes transactions while they’re in progress, preventing unauthorised transfers and account takeovers.
If you’re looking to strengthen your fraud controls with live mobile network intelligence, contact the JT Mobile Intelligence team.