Socure Identity Risk Insights: Government Fraud Patterns Report

Executive Summary

During the pandemic, fraud skyrocketed as government agencies attempted to get critical funds quickly out the door to people in need. Domestic and international crime rings took advantage of outdated verification methods – that relied on credit-header data or knowledge-based authentication – to flood government agencies with fraudulent applications. Not only were billions of dollars lost, but real applicants were blocked from the services they needed because they could not be validated by legacy systems, and sometimes fraudsters got to their benefits first.

Now, fraudsters view government agencies as easy targets and are continuing to exploit their vulnerabilities.

According to reports from the Government Accountability Office, fraud costs the federal government up to $500 billion annually.

Criminals are using the stolen identities of Americans to pilfer federal and state government programs at record pace. New, AI-enabled technologies allow bad actors to use increasingly sophisticated fraud tactics to siphon billions away from programs, hitting people at their most critical and often vulnerable moments: in the aftermath of a natural disaster, after becoming unemployed, or when launching their own small business.

And these attackers are not just individuals looking to put a few thousand dollars in their pockets – they are often sophisticated, organized crime networks that steal massive amounts of funds at scale. Researchers from Socure have tracked fraud rings originating in China, Russia, and around the world. And these criminals are getting more sophisticated, deploying techniques, such as the creation of synthetic identities, faster and in greater volume than ever before.

As Washington prioritizes efficiency, one of the most significant opportunities to reduce government waste, fraud, and abuse remains under-addressed: strengthening our digital identity verification systems.

For far too long, fraud has been seen as the cost of doing business in government. But this is a fallacy. With advanced technologies, government can deliver a seamless experience to real people while combating fraud and protecting taxpayer dollars. Across the country, some government agencies are beginning to adopt advanced digital identity verification methods that combine artificial intelligence with machine learning to verify all aspects of identity – and they’re seeing immediate impact. These adopters have reduced the presence of bot attacks, and fake accounts.

This report sounds the alarm on fraud in government programs. The message is clear: fraudsters are attacking government programs with relentless speed, using stolen and fake identities, across state borders and within agencies, often driven by complex crime networks that are difficult to entirely track down and stop.

As government services have become increasingly digital, the need for accurate digital identity verification has never been greater. In order to change the status quo, we must first understand how perpetrators of fraud operate.

Key Findings

This report uncovers a variety of fraud patterns used by domestic and international fraudsters against public sector agencies. Key findings include:

U.S. government programs are attacked by international fraud groups originating from China, Russia, Poland, India, South Africa, Philippines, and several other nations.
In conducting this research, Socure uncovered dozens of international fraud rings. Attacks ranged in frequency and origin depending on the time of day and government program. And international bad actors were responsible for between 2% and 12% of all incoming applications for government services and/or loans.
Fraudsters target multiple government agencies at once. At least 25.2% of fraud attempts targeted more than one agency.
Once a fraudster establishes an identity with the government, that identity can be used to attack multiple agencies at once.
Fraudsters prefer identity theft over synthetic identity fraud. Fraudsters are more likely to steal real identities rather than create fake ones, at a rate of almost (79.7% vs. 20.3%). This is likely in an effort to steal real people’s government payments or benefits.