CAMS Prep

Visa's Spring 2026 Biannual Threats Report identifies scams as the single largest category of consumer payment fraud.

🛡️ From July to December 2025, Visa flagged nearly $1 billion in scam-related activity across its global network in just six months.

🔍 Generative AI is now the primary scaling tool — producing deepfake audio and video, synthetic identities, and social engineering scripts that defeat traditional controls.

⚖️ The layering window has collapsed. Real-time payment rails compress the laundering cycle from weeks to hours.

🚨 Every institution processing real-time payments should be asking: How quickly can your transaction monitoring flag an anomaly after a fraud-driven credit?

🚫 Close the gap!

$4.4 trillion. That is the size of global financial crime in 2025 — larger than Germany's entire GDP.

Nasdaq Verafin's 2026 industry report puts illicit financial activity at a 19.2% annualized increase since 2023. U.S. banks alone absorbed $179 billion in direct fraud losses. The driving force:
🛡️ AI-powered criminal networks operating at scale
🛡️ Mexican cartels leveraging Chinese money laundering syndicates to move proceeds through American institutions.

This is not background risk; it is the current operating environment.

Of 500+ financial crime professionals surveyed:
🔍 90% report an increase in AI-driven attacks over the past two years.
🔍 The criminals did not wait for regulators to define the threat before deploying it.

The $4.4 trillion figure reflects that financial crime now has the institutional infrastructure of a major economy:
⚖️ Shell companies
⚖️ Synthetic identities
⚖️ AI-generated documentation
⚖️ Real-time payment rails
These are active risks, not just emerging ones.

Yet, 75% of surveyed professionals plan to expand AI investment for detection and response.
That is the right call, but the gap between where defenses are today and where the threat already is remains significant.

If AML hasn't reached your board agenda as a strategic risk discipline — not a compliance cost center — this number should be the reason it does.

$75 billion in criminal funds is stuck on-chain — and the balance is growing.

🛡️ Binance Research's May 2026 findings show illicit cryptocurrency balances rose 28% year-over-year, even as laundering routes are closing.

🔍 KYT monitoring, stablecoin freezing tools, and compressed mixer capacity are working. It now takes over 100 days to fully launder $1 billion through mixers alone. Bitcoin accounts for nearly 75% of all flagged illicit balances.

⚖️ Blockchain transparency is producing results that traditional correspondent banking surveillance never could. On-chain data trails are permanent, queryable, and increasingly hard to obscure.

💰 But $75 billion sitting idle is not a solved problem. It is pressure building inside the system. When new laundering routes emerge — and they will — those funds will move fast.

🏦 For institutions with any crypto exposure, the question is not whether illicit funds exist in the ecosystem. It is whether your monitoring infrastructure can detect movement before the exit. A clean SAR history is not the same as forward-looking crypto risk readiness.

📈 Under 1% of on-chain volume being illicit sounds reassuring until you do the math on what that dollar figure actually represents at current transaction volumes.

🔒 The institutions that invest in crypto risk infrastructure now won't be the ones explaining a missed detection to their examiner later.

A 22-year-old has been sentenced to nearly six years in federal prison for laundering $263 million in cryptocurrency.

This case serves as a typology alert for compliance teams, highlighting critical changes in recruitment methods within criminal networks:

🛡️ Young, digitally adept individuals are being targeted to orchestrate complex crypto laundering schemes.

🔍 They often lack the traditional risk profile, leading to underestimation of their legal exposure.

⚖️ Compliance programs must adapt customer risk profiles and transaction monitoring to consider high-volume transactions by young operators.

📊 The operation's scale underscores the sophisticated methods used, incorporating crypto mixing and chain-hopping.

💡 It’s essential to update your typologies and train frontline teams. The speed of change in financial crime profiles is accelerating, and many AML programs may not yet be prepared.

20 years. $73 million. One defendant.

But behind every sentencing headline, there is a more important question for compliance professionals: how did $73 million move through the financial system before anyone stopped it?

A defendant has been sentenced to 20 years in federal prison for running a global cryptocurrency investment fraud scheme that defrauded thousands of victims worldwide. Proceeds were laundered through layered accounts and shell structures across multiple jurisdictions — the kind of scheme that typically exploits gaps in correspondent banking oversight, weak beneficial ownership controls, and under-resourced SAR review processes.

The DOJ's willingness to pursue maximum penalties at this level is a deliberate signal.

🛡️ This is an escalation in deterrence posture for crypto fraud and money laundering cases — and it tells us something about what is coming for others still running similar operations.

For AML teams, the sentence is not the takeaway. The typology is.

🔍 Pig-butchering and crypto investment fraud continue to dominate AML caseloads globally. The proceeds movement patterns — layered wallets, cross-chain conversion, complicit accounts — are detectable with the right monitoring scenarios in place.

⚖️ Every enforcement action at this scale is a typology briefing. The question is whether your team treats it as one.

The 2026 U.S. National Money Laundering Risk Assessment (NMLRA) has been released! 📄 It's crucial for anyone involved in AML in the United States to read this report. 🔍

The NMLRA is a key document in U.S. AML practice used by examiners for reference. It sets the standards for BSA compliance expectations and your institution's risk assessment needs to reflect its findings. ⚖️

Key ML threats identified include:
🛡️ Drug trafficking proceeds
🛡️ Human trafficking
🛡️ Cybercrime
🛡️ Professional money laundering networks

There is specific attention on:
🏦 Cash-intensive business abuse
🏦 Real estate laundering
🏦 The rise of crypto-enabled layering schemes

This report also informs SAR guidance, examination standards, and how regulators will evaluate your institution’s risk appetite framework in future reviews. 🚨

Next steps: Pull your current risk assessment and compare it against the threat categories in this document. Areas where your coverage is inadequate will attract the most attention from examiners. ⚠️

For AML compliance leaders, making a case for program investment can be tough. This report supports that effort—it’s the U.S. government clearly stating the threat landscape and what is required for an adequate response. 📈

Read it. Align to it. Document your gap analysis. 📊

Source:https://home.treasury.gov/system/files/246/2026-NMLRA.pdf

$442 billion. That is what the world lost to fraud in 2025.

INTERPOL's 2026 Global Financial Fraud Threat Assessment has put hard numbers to what compliance professionals have been raising for years. Fraud now ranks among the top five global crime threats — and AI has fundamentally changed the economics of running a fraud operation.

🛡️ AI-enhanced fraud schemes are 4.5 times more profitable than traditional methods.
🛡️ Agentic AI systems can now autonomously execute complete fraud campaigns — from target identification to payment processing — without human intervention at every step.

🔍 Fraud-related INTERPOL Notices and Diffusions surged 54% from 2024 to 2025.
🔍 Criminal networks are operating with increasing coordination, pairing fraud infrastructure with specialized money laundering groups to create an industrialized pipeline from victim proceeds to clean funds.

⚖️ INTERPOL is responding with Operation Shadow Storm and a new Anti-Money Laundering Rapid Response Protocol for cross-border asset freezing. These are meaningful developments. But the window between proceeds generation and successful laundering continues to shrink.

⚖️ For AML and fraud teams, this assessment is a direct call to act. Fraud typologies, SAR narratives, and transaction monitoring thresholds need to reflect AI-enabled threat patterns — not benchmarks from three years ago.
⚖️ If your institution still treats fraud and AML as separate silos with no shared intelligence flow, that structural gap is now an exposure in itself.

The threat is not emerging. It is the operating environment.

Criminals are using AI to launder money—and they started before we did.

AUSTRAC, Australia's financial intelligence unit, issued a formal warning that organized crime is actively deploying artificial intelligence to automate money laundering:

🛡️ Generating synthetic identities
🛡️ Producing fraudulent documents that defeat traditional detection controls
🛡️ Running scam operations at a scale no human team could sustain

This is not a future scenario. It is happening right now.

What makes this alert significant is that it is one of the first from a major APAC financial intelligence unit to specifically identify AI as an operational tool being used by bad actors—not just a compliance investment for the good side.

The same capabilities AML teams are spending years and significant budgets to build, criminals have already deployed. The asymmetry is real and it is growing.

⚖️ Rule-based transaction monitoring was designed around human behavior.

🔍 AI-generated fraud patterns are faster, more varied, and more consistent than anything a human operator could produce manually.

⚠️ Static thresholds and legacy typologies are becoming increasingly inadequate.

Behavioral analytics, typology updates, and model governance are no longer aspirational program improvements. They are baseline requirements for any credible AML function.

Every AML conference in 2026 celebrates AI as the answer. This AUSTRAC alert is a reminder that the other side has the same tools—and they are not waiting for budget approval cycles.

🚨 The 2026 FIFA World Cup is approaching, prompting FinCEN to issue a vital alert for compliance officers in host cities.

🛡️ On May 11, the agency warned financial institutions in the U.S., Canada, and Mexico to be vigilant against human trafficking-related financial activities, specifically targeting:
- Dallas
- New York
- Los Angeles
- Kansas City
- Seattle
- Boston

🔍 Institutions are advised to update SAR procedures and participate in Section 314(b) information sharing, with updated red flags reflecting current threats.

⚖️ Major sporting events create spikes in cash-intensive hospitality activities, which traffickers exploit. These include hotel transactions, short-term rentals, ride-hailing, and entertainment spending.

🚩 Key behavioral indicators include:
- Guests paying in cash for extended stays
- Multiple individuals sharing one room with few personal belongings
- Large-volume prepaid card purchases

📚 Front-line staff training is critical. Customer-facing employees are often the first point of contact with potential victims or exploiters. A SAR based on behavioral observations can be more actionable than one triggered by algorithms.

🏁 If your institution operates in a World Cup host metro and you haven't updated your human trafficking red flag guidance recently, now is the time to act!

$51 billion in illicit stablecoin activity in 2024 alone. The FATF President is no longer speaking in hypotheticals.

FATF President Elisa de Anda Madrazo named stablecoins — particularly Tether — as a key driver of global fraud, describing the growth as "exponential." Speaking on the AML Intelligence Collared podcast, she highlighted how P2P platforms and unhosted wallets create dangerous blind spots for financial intelligence units worldwide, calling for AML obligations to be extended to unregulated virtual asset service providers.

This is not a general crypto warning. The FATF President is specifically naming stablecoins, with figures that should concern every AML team.

🛡️ Stablecoin rails have become the preferred settlement layer for fraud networks because they:
- move fast,
- cross borders,
- largely sit outside traditional correspondent banking oversight.

$51 billion is not an edge-case statistic. It points to a systemic gap in the global financial system.

For AML programs, the practical implication is clear:
- If your typologies library does not have a dedicated stablecoin section, it is behind the regulatory curve.
- Risk assessments treating all virtual assets as a single category need to be disaggregated.
- Stablecoins require specific red flags, controls, and escalation logic.

⚖️ VASP due diligence standards need immediate review. The FATF president's comments indicate that scrutiny of unhosted wallet exposure will intensify sharply through 2026.

If your AML program does not have a stablecoin typology, building one is now a documented regulatory expectation.