Opinion argues a trillion-dollar fraud problem is helping fund U.S. adversaries

When fraud turns into a national risk

Fraud against government programs is not just “waste.” GAO says the federal government loses hundreds of billions to fraud each year. The scale has grown quietly over time.

When that money gets stolen, it can be moved, laundered, and reused fast. Treasury’s national risk assessments warn that illicit financial flows pose a real security risk. Those risks now extend well beyond budgets.

The scale is already staggering

GAO’s first government-wide estimate puts annual fraud losses between $233 billion and $521 billion. That range is based on fiscal years 2018–2022 and reflects different risk years. Even the low end is historically large.

On top of that, GAO tracks “improper payments,” which can include errors and fraud. Agencies reported $162 billion in improper payments for FY2024, and GAO says totals since 2003 are about $2.8 trillion. These totals span multiple administrations.

Fraud vs. improper payments, explained

Fraud is theft, like fake identities, shell companies, or billing for services that never happened. Improper payments are broader, like payments made in the wrong amount or to the wrong person. The two often overlap in practice.

That distinction matters because some “improper” dollars are true mistakes, and some are criminal. Either way, the taxpayer loses, and trust drops when basic controls fail. Public confidence erodes quickly.

Speed is the fraudster’s best friend

During COVID, programs scaled fast, and criminals followed the money. GAO estimates pandemic unemployment insurance fraud was likely $100 billion to $135 billion. Emergency systems were built under pressure.

The SBA inspector general estimated over $200 billion in potentially fraudulent COVID relief across EIDL and PPP-related programs. When systems pay first and check later, scammers treat it like a business model. That model still attracts copycats.

Paying dead people is still a problem

One fix sounds basic: use death data to stop payments that should never go out. GAO has pointed to making SSA’s full death data easier to use across government payment checks. Data silos remain a hurdle.

Treasury’s “Do Not Pay” tools are meant to help block improper payments before they happen. But they only work well when agencies share clean, complete data in real time. Gaps weaken the system.

Self-attestation is a giant loophole

Many benefit and provider systems still rely on “tell us who you are” onboarding. Fraudsters exploit that, then disappear long before audits catch up. GAO has repeatedly warned that weak prevention leads to repeated losses. The pattern keeps repeating.

This is why verification timing matters. A check after the money is gone is not protection; it is paperwork. Prevention has to happen before the payment clears. Late checks rarely recover funds.

GAO says agencies can’t prove fixes work

GAO says agencies often cannot determine whether anti-fraud efforts are working. That is a big deal, because you can’t manage what you don’t measure. Without clear benchmarks, failures stay hidden. Metrics are often incomplete.

Fraud controls should be tested like any other system. If a tool is not reducing losses, agencies need to know quickly, not years later. Delayed feedback allows the same weaknesses to persist. Delays compound damage.

Prevention looks boring, and that’s good

Banks and card networks use identity checks, velocity rules, and risk scoring every day. Government programs can use similar ideas without cutting benefits. These approaches are standard across modern finance. These tools are already proven.

GAO’s fraud work emphasizes stronger risk management and data analytics. The goal is simple: stop obvious bad payments before they leave the Treasury. Prevention costs far less than recovery. Early stops save resources.

Illicit money doesn’t stay local

Fraud proceeds don’t just sit in one state or one account. Treasury’s risk assessments describe how money laundering moves through layered transactions and cross-border networks. Those networks are highly organized.

That makes fraud more than a budget issue. Once stolen funds enter illicit pipelines, they can support organized crime and other high-risk activity. The consequences escalate quickly.

Fintech apps are now real money rails

Payment platforms are not just “apps” anymore, they are financial infrastructure. Many fall under money services business rules, with Bank Secrecy Act reporting and AML program obligations. Their reach is massive.

But fast onboarding and high volume can create blind spots. When transaction speed beats oversight, criminals look for the weakest link. Gaps rarely stay hidden.

Cash App penalties

Regulators have fined Block Inc. over anti-money laundering and compliance failures tied to Cash App. Reuters reported an $80 million multistate settlement and a separate $40 million New York fine. The penalties drew national attention.

Those cases highlight a simple lesson. If compliance gaps can exist at massive scale, bad actors will try to ride that scale too. Scale attracts risk.

Taiwan’s $975M laundering case hits home

In January 2026, Taiwanese prosecutors indicted 35 people in a case involving about NT$30.6 billion (around US$975 million) in alleged laundering tied to illegal online gambling.

Reports say the payment platforms they controlled helped move the money. The operation ran for years. That is not “over there” news. It shows how custom payment rails can quietly scale illicit flows for years. The model is transferable.

In other news, Maryland’s unemployment system faces scrutiny over billions in losses and failures.

Guardrails that actually slow fraud

Start with identity proofing before enrollment, not after payment. Add stronger provider checks, ownership verification, and real service confirmation. These steps reduce exposure early.

Then link the data across agencies, so scammers can’t reset under a new name. GAO and Treasury both point to data-sharing and modern analytics as core tools. Fragmentation helps criminals.

Read next how Minnesota’s Medicaid fraud scandal reveals a far more complex problem and the results of government oversight.

What do you think is the smartest fix first: stronger ID checks, better data sharing, or tougher penalties, and why? Share your thoughts and your view in the comments.

This slideshow was created with AI assistance and human editing.

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