How the UK is tackling industrialized crypto fraud

Global illicit financial activity reached an estimated $4.4 trillion in 2025, according to Nasdaq Verafin's Global Financial Crime Report, and crypto-enabled scams alone could reach as much as $17 billion, according to the latest Crypto Crime Report.

And the average victim is losing more than ever: the typical scam payment surged 253%, from $782 in 2024 to $2,764 in 2025, as criminal operations became more convincing and significantly more ruthless.

The reasons why are unfortunately clear. Scams are now run by networks that operate like corporations, with different actors specializing in victim data acquisition, social engineering, and laundering proceeds.

Crypto, particularly stablecoins through which 84% of illicit activity now flows, gives criminals both liquidity and speed to extort and launder.

Meanwhile, AI, when deployed as part of scams, makes them 4.5 times more profitable per operation than those relying on conventional methods. Nowhere is this more apparent than in impersonation scams, where fraudsters pose as trusted organizations or authority figures, which exploded by 1,400% in 2025 alone.

This is a transnational security challenge that cuts across cybercrime, organized crime, and economic resilience, and reactive enforcement built around individual cases cannot keep pace with criminals who move as freely as data does.

Too big a problem to police the old way

Fraud now accounts for 45% of all crime in the UK, according to the government's Fraud Strategy 2026 to 2029, costing the economy an estimated £14 billion a year, yet has historically received less than 1% of policing resources.

Around 75% of fraud against UK individuals and businesses is instigated or facilitated from overseas, and City of London Police data shows that crypto plays a role in two-thirds of all reported investment fraud.

The deeper problem is structural. For decades, enforcement responsibilities have been split across local police forces, national agencies, financial regulators, and telecoms providers, each holding fragments of the picture but none able to see the whole network.

The speed of criminal innovation is outpacing the response: 90% of financial crime professionals surveyed by Nasdaq Verafin reported an increase in AI-driven attacks at their institution over the past two years, and fraud infrastructure has scaled far faster than the institutions designed to stop it.

UK enforcement is catching up

In 2025, the Metropolitan Police secured convictions in a landmark crypto money laundering case, linked to a multibillion-pound fraud originating in China, leading to the recovery of over 61,000 bitcoin, worth approximately £5 billion, and the world's largest confirmed crypto seizure.

Blockchain analytics were central to the investigation, enabling officers to trace the movement of funds across thousands of wallets.

But because most fraud targeting the UK originates overseas, domestic enforcement alone will never be enough.

Public-private partnerships: Collaborating, not just cooperating

Jointly run by the UK National Crime Agency, the US Secret Service, and Canadian authorities, this operation acts as rare proof that public-private partnerships can be more than talking points. It brought law enforcement, blockchain intelligence firms, and crypto exchanges together at NCA headquarters to disrupt approval phishing scams in real time.

It built on the methodology pioneered by Project Spincaster, an initiative that used blockchain analytics to proactively identify compromised wallets before they are drained, rather than waiting for victims to report losses after the fact.

The model works like this: on-chain analysis identifies wallets where a victim has unknowingly granted a scammer permission to spend their tokens, but the scammer has not yet acted, creating a window to contact the victim, revoke the approval, and freeze proceeds before they can be laundered. It is the difference between investigating a crime scene and preventing a crime in progress.

Over the course of a single operational sprint, teams identified more than 20,000 victims across the UK, Canada, and the United States, froze over $12 million in suspected criminal proceeds, and traced more than $45 million in stolen cryptocurrency linked to fraud schemes worldwide. One UK victim, targeted through a fake investment platform, was believed to have lost upwards of £52,000 before investigators intervened.

What makes this model significant is not just the results, but the structure. Law enforcement provided the legal authority and coordination. Blockchain intelligence provided the on-chain data and tracing. Crypto exchanges executed the technical freezes that stop scammers from converting crypto into cash. Thai was not just co-operation, but close collaboration, and the result was disruption at a speed and scale that no single agency or company could achieve alone.

Operations like these alongside joint UK-US sanctions and the seizure of more than $15 billion linked to the Prince Group (a transnational organisation running forced-labor scam compounds in South East Asia) confirm that for scammers, out of sight is no longer out of reach.

Domestic reform as a blueprint

The UK's Fraud Strategy 2026 to 2029 recognized fraud as a system-wide problem - spanning banks, fintechs, crypto businesses, telecoms, and online platforms - and committed £250 million in new resources. Central to this is the Online Crime Centre, a new public-private partnership backed by £31 million in government funding, designed to fuse data from policing, intelligence agencies, and industry to build a shared operational picture of how criminals operate and coordinate disruption in real time.

Operationally, the replacement of Action Fraud with Report Fraud matters because it attacks the siloed model directly. The new national reporting service is designed to rapidly triage cases, identify patterns, and generate actionable intelligence, so that a single crypto address appearing across dozens of victim reports can quickly map out an entire criminal network.

The creation of the National Fraud Squad, with approximately 400 dedicated officers, reinforces the shift. These reforms are overdue, Action Fraud was widely criticized for years, and decades of fragmented enforcement left the UK badly exposed to a threat that was industrializing faster than anyone anticipated. But the direction is right: moving from volume-based case handling towards intelligence-led, data-driven investigation, the kind of approach that Operation Atlantic has already proven works.

Crucially, this is not just about imposing obligations on the private sector; it is about creating the frameworks and incentives that make collaboration worthwhile. Operation Atlantic showed what happens when companies are given a meaningful seat at the table: faster intelligence, faster freezes, and outcomes that no single agency could deliver alone. The challenge for policymakers is to make that the norm, not the exception.

From detection to disruption

The old model, characterized by siloed agencies, reactive investigations, and cases pursued one at a time, was built for a world where fraud was local and slow. It cannot survive contact with industrialized, cross-border scam operations that scale to thousands of victims in days.

The UK is beginning to replace that model with something faster and more connected. Operation Atlantic and the Spincaster model are not just case studies; they are proof that data-led collaboration can move faster than the criminals it targets.

But strategy documents do not stop scammers. The real test is whether these commitments translate into faster disruption of live operations and earlier intervention, before people become victims and lose their money.

Crypto-enabled fraud is growing in scale, sophistication, and human cost. But crypto is not just the problem; it is firmly part of the solution. The same blockchain transparency that criminals exploit can help investigators trace networks, identify illicit actors, and intervene earlier.

The UK has laid the groundwork, but the question remains: can it learn from past endeavors and harness the technology and collaboration needed to deliver at the speed the threat demands?

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