Write an article about
Key points:
In today’s schools, whether K-12 or higher education, AI is powering smarter classrooms. There’s more personalized learning and faster administrative tasks. And students themselves are engaging with AI more than ever before, as 70 percent say they’ve used an AI tool to alter or create completely new images. But while educators and students are embracing the promise of AI, cybercriminals are exploiting it.
In 2025, the U.S. Department of Education reported that nearly 150,000 suspect identities were flagged in recent federal student-aid forms, contributing to $90 million in financial aid losses tied to ineligible applicants. From deepfakes in admissions to synthetic students infiltrating online portals and threatening high-value research information, AI-powered identity fraud is rising fast, and our educational institutions are alarmingly underprepared.
As identity fraud tactics become more scalable and convincing, districts are now racing to deploy modern tools to catch fake students before they slip through the cracks. Three fraud trends keep IT and security leaders in education up at night–and AI is supercharging their impact.
1. Fraud rings targeting education
Here’s the hard truth: Fraudsters operate in networks, but most schools fight fraud alone.
Coordinated rings can deploy hundreds of synthetic identities across schools or districts. These groups recycle biometric data, reuse fake documents, and share attack methods on dark web forums.
To stand a fair chance in the fight, educational institutions must work with identity verification experts that enable a holistic view of the threat landscape through cross-transactional risk assessments. These assessments spot risk patterns across devices, IP addresses, and user behavior, helping institutions uncover fraud clusters that would be invisible in isolation.
2. Deepfakes and injected selfies in remote enrollment
Facial recognition was once a trusted line of defense for remote learning and test proctoring. But fraudsters can now use emulators and virtual cameras to bypass those checks, inserting AI-generated faces into the stream to impersonate students. In education, where student data is a goldmine and systems are increasingly remote, the risk is even more pronounced.
In virtual work environments, for example, enterprises are already seeing an uptick in the use of deepfakes during job interviews. By 2028, Gartner predicts 1 in 4 job candidates worldwide will be fake. The same applies to the education sector. We’re now seeing fake students, complete with forged government IDs and a convincing selfie, slide past systems and into financial aid pipelines.
So, what’s the fix? Biometric identity intelligence, trusted by a growing number of students, can verify micro-movements, lighting, and facial depth, and confirm whether a real human is behind the screen. Multimodal checks (combining visual, motion, and even audio data) are critical for stopping AI-powered identity fraud.
3. Synthetic students in your systems
Unlike stolen identities, synthetic identities are crafted from real–and fake–fragments, such as a legit SSN combined with a fake name. These “students” can pass enrollment checks, get campus credentials, and even apply for financial aid.
Traditional document checks aren’t enough to catch them. Today’s identity verification tools must use AI to detect missing elements, like holograms or watermarks, and flag patterns including identical document backgrounds, which is a key sign of industrial-scale fraud.
AI-powered identity intelligence for education
As digital learning becomes the norm and AI accelerates, identity fraud will only get more sophisticated. However, AI also offers educators a solution.
By layering biometrics, behavioral analytics, and cross-platform data, schools can verify student identities at scale and in real time, keeping pace with advancing threats, and even staying one step ahead.
Ashwin Sugavanam, Jumio Corporation
Ashwin Sugavanam is currently the VP, AI & Identity Analytics at Jumio Corporation. Ashwin is a visionary Data and Analytics leader with two decades of overall experience out of which he has spent the last decade in helping organizations incubate and scale Data & AI practices. Over the last couple of years Ashwin has helped organizations drive measurable business outcomes by responsibly scaling Data and AI initiatives, implementing modern concepts like Data Mesh and MLOps, and leveraging tools such as the Data Scientist Co-Pilot to accelerate impact. He can be reached on LinkedIn and at the company website https://www.jumio.com/ .
Latest posts by eSchool Media Contributors (see all)
.Organize the content with appropriate headings and subheadings ( h2, h3, h4, h5, h6). Include conclusion section and FAQs section with Proper questions and answers at the end. do not include the title. it must return only article i dont want any extra information or introductory text with article e.g: ” Here is rewritten article:” or “Here is the rewritten content:”
