Stemming the flow of fraudulent activity in government has always been a challenging task due to limited resources and manpower. But now, the onslaught of fraud has become a firehose of unprecedented scale, enabled by AI-driven attacks. This escalation places an inordinate strain on already stretched resources, making it critical for government agencies to adopt AI-powered tools to prevent and mitigate fraud effectively. In fact, according to a new global research report from SAS and Coleman Parkes, tackling fraud, waste and abuse (FWA) could save governments 16% of their budget.
As AI evolves, fraudsters increasingly misuse it to scale sophisticated attacks, overwhelming traditional defenses. The stakes are high: public trust, economic stability and global security. Governments must adopt AI-driven tools — not just to keep pace but to turn the tide. In this AI-powered arms race, governments must embrace advanced analytics and AI solutions, transforming these technologies from tools of fraud into shields of resilience.
The rise of AI-powered fraud
Per the report, 95% of global government agencies surveyed have experienced AI-powered FWA schemes. Fraudsters now deploy AI-powered platforms to generate synthetic identities, craft hyper-personalized phishing campaigns, and design malware that evades detection. These tools analyze vast datasets to mimic human behavior, forge documents and exploit vulnerabilities in real time. For instance, generative AI can create fake passports or invoices that are indistinguishable from genuine ones, enabling fraudsters to infiltrate financial systems or manipulate procurement processes.
AI also allows scams to scale exponentially. Phishing campaigns can now deploy thousands of convincing emails in seconds. Synthetic identities — built using real and fabricated data — bypass traditional checks, enabling fraud rings to claim benefits or open fraudulent accounts across jurisdictions. Meanwhile, AI-driven malware adapts to evade outdated security systems, surging ahead of human-led defenses.
Deepfakes are even showing up in virtual meetings, with AI used to imitate trusted colleagues, as cited in a recent Fortune article, “In a chilling example from January 2024, an employee at a Hong Kong-based firm was tricked into sending $25 million to fraudsters after participating in a video call with what she believed were her colleagues, including the CFO. In reality, the entire call was a sophisticated deepfake created by scammers.”
Government’s uphill battle
Faced with surging workloads, limited budgets and often outdated systems, how can government agencies confront these threats? According to the report, only 1 in 10 agencies have all the tools and resources they need to fight FWA, and nearly 1/3 face significant resource limitations. Outdated manual processes can create backlogs that fraudsters exploit.
Tax agencies struggle with massive volumes of real and fake return filings, procurement fraud drains public funds, and citizens lose trust in institutions when scams exploit vulnerabilities. Without AI-powered defenses, governments remain reactive and always one step behind.
Fraud also takes a toll on public confidence. Of the 1,100 survey respondents, all public sector employees responsible for monitoring FWA within their organizations, a staggering 96% say FWA has negatively impacted citizen trust in their agency and its programs.
The AI defense toolkit
Unencumbered by things like regulations and the law, AI-powered fraudsters may seem to have the upper hand, but maybe not for long. The near future looks promising. The research indicates that the use of machine learning for fraud detection is expected to expand from 36% to 84%. Even more encouragingly, 30% of respondents currently use GenAI solutions but over 90% expect to use GenAI in the next two years.
Advanced analytics and AI can play a pivotal role in this defense strategy. By combining data into a single dataset, software tools can analyze that massive amount of data and detect anomalies and hidden patterns indicative of fraud. This enterprise approach enables earlier and more precise detection of fraudulent activities, reduces investigation costs by minimizing false positives, and enhances the efficiency and productivity of inspectors.
In payment fraud detection, machine learning models combine behavior profiling with rules-based detection in a layered fraud prevention approach. These models use advanced methodologies and statistical techniques to identify risky transactions, flagging them for further review while reducing friction for legitimate users.
In law enforcement, analytics tools can connect disparate pieces of data, uncovering networks of fraudulent activities. For example, linking property records with benefit claims might expose synthetic identities, while AI analysis of whistleblower tips can prioritize high-impact investigations. This integration capability not only accelerates case resolution but also ensures fraud detection systems adapt to evolving threats.
The stakes of the AI arms race
Generative AI’s market is projected to reach $1.3 trillion USD by 2032. This growth is a double-edged sword: While the technology has the unfortunate side effect of empowering fraudsters, it can also equip governments with the tools to dismantle their schemes. Urgency is key. Agencies delaying AI adoption risk being overwhelmed by increasingly sophisticated attacks.
The AI arms race has reached the field of fraud, with AI now serving as a primary tool for fraudsters to exploit vulnerabilities while governments strive to keep pace. Yet AI also offers a solution: advanced platforms that automate detection, uncover hidden connections, and act in real-time.
Governments must invest in AI-driven defenses now or face higher costs in lost funds, eroded trust and unmanageable risks. Fortunately, the research indicates that this is happening, and agencies are better equipping themselves to fight back. In this race, innovative and tactical applications of AI tools will be the difference between leading the fight or falling behind.
Carl Hammersburg manages the government and healthcare risk and fraud team at SAS. Prior to that, he spent 20 years in anti-fraud activities for Washington State’s exclusive workers’ comp insurer, the Department of Labor and Industries. In 2004, Carl formed that agency’s comprehensive fraud program, covering tax and premium audit, claim investigation, provider fraud and collections.
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