Use stolen or fake identities to enroll in classes to pocket financial aid dollars

Colleges across the country are increasingly being targeted by fraudsters who use stolen or fake identities to enroll in classes and collect financial aid. For example, at Century College in White Bear Lake, Minnesota, officials estimate that as many as 15% of students in one class were part of what has been described as “an organized crime ring” exploiting this scheme.

According to a report by Erin Adler in the Minnesota Star Tribune (April 12, 2025), investigators found that most of the fraudsters reside in other countries. They typically enroll in online, asynchronous courses—those that allow students to access content at any time—primarily at two-year colleges, with no intention of learning or completing a degree.

“They try to make it through the early days of a course without being found out, doing the bare minimum in classwork until financial aid money is disbursed, usually about 10 days into the semester,” officials explained.

If the fraudsters remain enrolled by the second week, they receive loan disbursements, leaving the college—and ultimately taxpayers—responsible for repayment. In cases where a stolen identity is used, it is possible that the burden may fall on the unsuspecting victim. 

Students involved in the scheme may drop the class after receiving financial aid or remain enrolled, ultimately failing. They often continue registering for additional classes under the same name or identity until they are suspended or otherwise removed.

In one notable case, fraudsters targeted the College of Southern Nevada (CSN), leaving the institution responsible for millions in losses. The perpetrators enrolled as transfer students, a group subject to less rigorous vetting than first-time enrollees. Once classes began, instructors reported full rosters but empty classrooms. An external audit revealed that CSN incurred a $7.43 million debt related to the “ghost students” scheme, including tuition, fees, and institutional write-offs. Additionally, CSN was required to repay the U.S. Department of Education for federal loans disbursed to the fraudulent students.

The ghost student epidemic has affected numerous colleges across the country. Notable examples include:

Prince George’s Community College, Maryland: In 2024, fraudsters submitted 80 fake applications in a single day—averaging one every seven minutes over the course of several hours. A college representative claimed that such fraudulent applications have become a routine challenge.

Pierce College, California: After identifying and removing ghost students from its enrollment rolls, the college saw a 36% decline in reported enrollment, dropping from 7,658 to 4,937 students. Fraudulent enrollments can artificially inflate student counts, disrupting resource allocation and course availability. Detecting and removing these cases often requires labor-intensive manual reviews.

Iowa Western Community College: Faculty members noticed suspicious student behavior, prompting an investigation that ultimately led to the detection and prevention of 109 fraudulent enrollments aimed at exploiting the financial aid system.

In January 2024, a spokesperson for the California Community Colleges Chancellor’s Office reported that approximately 25% of college applications were fraudulent—up from 20% in 2021.

As the threat continues to grow, many institutions are implementing new measures to combat fraud. Here are a few recommended strategies:

Require identity verification

Online identity verification tools can quickly collect and analyze identifying information from applicants. Combining a government ID verification with a selfie is a commonly used approach for fighting fraud. 

• Government ID verification: Applicants upload a picture of an approved government-issued ID, such as an identification card, driver’s license, or passport. The IDV tool analyzes the image for signs of authenticity, editing, and document tampering. It also extracts data from the ID that will be used for verification. 
• Selfie verification: With selfie identity verification, the applicant takes and uploads selfies or a short video and their face is compared to the image on the government ID. In the age of AI-generated selfies, liveness detection and advanced analysis are crucial for verifying the selfie is genuine. 

Passive database checks can also be performed in the background to verify information from the government ID without adding friction. Schools may also automatically run checks against internal databases to look for duplicate information or other red flags. 

Monitor passive and behavioral risk signals

Various types of passive signals, monitoring, and reports can help you uncover fraudulent applicants and ghost students without asking for more information or interfering with an application.

• Passive signals: Information from the applicant’s device or browser can help you uncover suspicious data points or patterns. These might include whether they’re using a VPN, their device’s IP address, location, and time zone, and if they are all out of sync with each other and not close to the address extracted from a driver’s license.
• Behavioral signals: Monitor how someone interacts with your application — whether they copy and paste information, use autofill, appear distracted, or use their mouse or keyboard in an unusual way. 
• Email risk reports: An email risk report can tell you when the email was first seen, most recently seen, whether it’s from a temporary mail service, when the domain was created, how active it is, and other information related to the potential risk associated with the email address. The results may be summarized with a risk score or recommendation. 
• Phone risk reports: Similarly, phone risk reports help you understand the risk associated with a phone number based on factors like the phone type, carrier, recent usage, and whether the number or SIM card was recently moved. 

These signals and reports can help you determine whether you should approve an application, deny it outright, request additional identification, or have someone manually review it.