Artificial Intelligence (AI) has become an integral part of today’s educational system, from K-12 to higher education, transforming classrooms into more intelligent and personalized spaces. More and more students are embracing AI tools, with 70 percent admitting to using AI to modify or create images. However, this growing embrace of AI is not without its risks, as cybercriminals are exploiting AI for identity fraud.
Rise of AI-Powered Identity Fraud in Education
As reported by the U.S. Department of Education in 2025, nearly 150,000 suspicious identities were flagged on federal student aid forms, leading to $90 million in financial aid losses due to ineligible applicants. The rise of AI-powered identity fraud, from admissions deepfakes to synthetic students infiltrating online portals, is a growing concern for our educational institutions, which are alarmingly underprepared for this emerging threat.
As these fraudulent tactics become more scalable and sophisticated, schools are seeking advanced tools to identify fake students before they can cause harm. Three prominent fraud trends amplified by AI are particularly worrying for education IT and security leaders.
Fraud Rings Targeting Education
Fraudsters often operate in networks, while most schools are left to fight fraud alone. Coordinated rings can deploy hundreds of synthetic identities across schools or districts, recycling biometric data, reusing fake documents, and sharing attack methods on dark web forums.
To effectively combat these threats, educational institutions must partner with identity verification experts who can provide a comprehensive view of the threat landscape through cross-transactional risk assessments. These assessments can identify risk patterns across devices, IP addresses, and user behavior, helping institutions uncover fraud clusters that would be invisible in isolation.
Deepfakes and Injected Selfies in Remote Registration
Previously, facial recognition was a reliable defense for distance learning and test proctoring. However, fraudsters can now bypass these controls using emulators and virtual cameras to insert AI-generated faces into the stream, impersonating students. In the education sector, where student data is a veritable goldmine and systems are increasingly remote, this risk is significantly heightened.
Companies in virtual work environments are already witnessing an increase in the use of deepfakes during job interviews. Gartner predicts that by 2028, one in four applicants worldwide will be fake. This alarming trend is not limited to the corporate world; the education sector is also witnessing fake students slipping past systems and into financial aid pipelines with fake government IDs and convincing selfies.
Synthetic Students in Your Systems
Synthetic identities, unlike stolen ones, are created from a blend of real and fake fragments, such as a legitimate Social Security Number combined with a fake name. These “students” can pass matriculation exams, receive campus transcripts, and even apply for financial aid. Traditional document checks are not sufficient to detect these frauds. Modern identity verification tools need to leverage AI to detect missing elements such as holograms or watermarks and flag patterns including identical document backgrounds, a key sign of industrial-scale fraud.
AI-Powered Identity Intelligence for Education
With the digitalization of education and the rapid evolution of AI, identity fraud is becoming increasingly sophisticated. However, AI also offers a solution to educators. By combining biometrics, behavioral analytics, and cross-platform data, schools can verify student identities at scale and in real-time, staying abreast of, and even ahead of, the increasing threats.
The author, Ashwin Sugavanam, is currently VP, AI & Identity Analytics at Jumio Corporation. With two decades of experience, Ashwin has spent the last ten years helping companies develop and scale data and AI practices, achieving measurable business results by responsibly scaling data and AI initiatives.
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