TL;DR

• Telcos are blocking record scam volumes – but losses keep rising.

• Blocking was a vital first step, yet scammers are adapting faster.

• Over-blocking brings false positives and trust risks.

• Networks need real-time intelligence that builds on what blocking started.

When Blocking Became the Benchmark for Progress

In 2019, Australia’s largest telco blocked just a few million scam calls a month.
Today, that number is closer to 18 million calls and 8 million scam texts each month [Commsrisk, 2025].

Across the world, results sound similar. In 2023, one of the largest US telcos blocked almost 20 billion scam calls in the US – and still, phone-fraud losses hit roughly US $10 billion [T-Mobile Report, 2024].

These are impressive numbers. Blocking works, and it has built customer confidence and regulatory trust. But it also exposes a gap: stopping calls isn’t the same as stopping scams.

As scammers automate and diversify, traditional filters are fighting a moving target. The industry isn’t failing – it’s reaching the limits of a successful first phase.

Why Blocking Alone Can’t Scale Forever

Blocking is popular for good reason. It’s measurable, defensible, and visible.
It gives telcos tangible proof of intervention – the kind of metric regulators and boards can rally behind.

Yet every blocked call is reactive. It prevents exposure but doesn’t touch the underlying scam infrastructure.
And as the volume of blocked traffic rises sixfold, each marginal gain gets harder to achieve.

Even fraud teams acknowledge the fatigue. A Telenor specialist put it bluntly: “We now flag one-third of all calls as fraudulent and block them. This is not sustainable.” [Commsrisk, 2025].

Blocking has done its job, so the next step is making it smarter.

How Scammers Adapt Faster Than Filters

Every time a network closes one route, scammers open another.
Spoofing has evolved into a flexible, multi-channel system that can pivot in hours.

• Number rotation: In Spain, mandatory verification rules under Order TDF/149/2025 drove the blocking of 48 million fraudulent calls and 2.2 million scam SMS within months [Spanish News Today, 2025].

• Cross-border injection: Italy’s AGCOM now blocks foreign calls pretending to be local [MEF, 2025].

• Smishing: Australian operators blocked ≈ 11 million scam SMS per month, up 69 % year-on-year [Telstra Senate Submission, 2024].

• OTT migration: India’s TRAI warned that scams are “rapidly migrating to encrypted apps” [Times of India, 2024].

The Cost of Over-Blocking

As filters grow stricter, legitimate traffic sometimes gets caught.

• False positives: Telstra told Parliament its Scam Filter occasionally captures legitimate messages that resemble scam patterns, prompting constant tuning [Telstra Senate Submission, 2024].

• Operational load: Each mis-flagged call requires review, driving cost and customer friction.

• Trust erosion: Ofcom warns that spoofing and inconsistent blocking “reduce trust in telephone calls, meaning even legitimate calls may be declined.” [Ofcom, 2025].

Blocking remains essential, but for the most part it’s a blunt instrument. The goal now is to achieve precision without compromise – maintaining safety while protecting legitimate communication.

Building on Blocking: The Intelligence Layer

Leading carriers are already extending blocking with real-time intelligence – a continuous feedback loop that learns from live traffic rather than static rules.

Case Study – Apate Intelligence Layer Deployment

In a recent Asia-Pacific deployment, a major regional carrier transformed how it fights scams by integrating a fleet of conversational AI bots directly into its network. Instead of simply stopping calls at the gate, the carrier could now interrogate and validate scam traffic in real time – generating intelligence that was instantly fed back into its detection models.

The result was a fundamental shift in capability. Defences became self-improving, scam signals became clearer, and network performance became smoother. Most importantly, the carrier unlocked visibility into scam operations that had never before been possible – intelligence that revealed who was calling, how they were adapting, and how their operations could be dismantled upstream.

This marked a turning point in network defence: moving from passive blocking to active disruption.

From Data to Disruption

The value didn’t stop at stronger filters. By engaging directly with scam traffic, the carrier gained deep operational insight into how scam networks function – and how to stay several steps ahead.

This included:

• Patterns that exposed peak operating windows and high-risk activity zones
• Intelligence on 1,000+ impersonated organisations
• Unprecedented real time insights into live scam campaigns, allowing for downstream intelligence sharing.  
• Insights into evolving scam typologies across the network

‍

These insights fuelled continuous detection improvements, more accurate reporting, and early regulatory alerts. They also gave the carrier a strategic edge: visibility into the scam economy that no blocklist alone could ever deliver.

Collaboration is the Next Competitive Advantage

Intelligence multiplies when shared.

• In Australia, Telstra and Commonwealth Bank exchange live scam indicators to stop fraudulent transfers mid-call–a programme credited with “helping protect customers from losing millions” [Telstra Media Release, 2024].

• The National Anti-Scam Centre has reported a 25.9% drop in scam losses after coordinated data-sharing between telcos, banks, and platforms [Mobile World Live, 2025].

Regulators are leaning the same way. Ofcom and the FCC are both prioritising cross-network tracing and intelligence exchange over isolated blocking campaigns.

The Way Forward

Blocking built the foundation. Now it’s time to build on it.

Real-time intelligence helps networks see patterns earlier, reduce false positives, and act before customers are exposed.
It transforms blocking from a static shield into a live sensor grid – one that learns, adapts, and informs.

The future of scam defence isn’t about stopping more calls. It’s about understanding them.
When networks move from counting blocked calls to measuring prevented harm, scams become harder to run, harder to scale, and harder to hide.

Sources: This analysis draws on operator and regulator disclosures together with industry research, principally T-Mobile’s Scam Reports (2022–2023) for large-scale blocking volumes; the Communications Fraud Control Association (CFCA) Global Fraud Loss Surveys for historical telecom-fraud loss estimates; Juniper Research robocall forecasts for 2023–2025 projections; Telstra corporate updates (Cleaner Pipes) for Australia-level blocking time series; ACMA quarterly reports and the Australian industry code monitoring for national aggregate blocking totals; and the National Anti-Scam Centre / ACCC “Targeting Scams” reporting for outcomes from cross-sector data-sharing. Where direct annual totals were unavailable, adjacent published figures and authoritative forecasts were used to produce conservative, clearly annotated estimates.