Education loan fraud by criminals who pose as students just keeps getting worse. The victims? Schools with distance learning programs. With a purely virtual student population, it’s extremely difficult to know who, exactly, is really logging in to the LMS.
Estimates by the Office of Inspector General in 2013 put fraud at $874M with a huge increase of 82% between 2009 – 2012. An estimated 4% of all loan funds dispersed may be fraudulent. We haven’t even SEEN estimates for the last few years so loan losses are undoubtedly much higher.
Who’s on the hook? Online learning institutions. And it’s not going to get any better until schools are able to detect and prove students are fake before lending them money.
This could all be solved easily with air-tight student authentication and the ability to monitor for the signals of fraud.
Advance warning is the ONLY way to prevent this scam. The issue is that schools face a bind. With virtual registration, they don’t really know who anyone actually is. Fake students enroll for classes, apply for loans, receive loans…then drop out and vanish.
Some may not even bother to drop out but never complete the course work. They’re known as Pell Runners. Often they enroll under identities that are actually stolen, causing huge problems for the victim. Often they move from college to college, picking up funds then moving on.
Because there is not master database to track these actions between schools, these fraudsters can operate with impunity. And every school is a new mark.
Ready to find out how to recover loan losses?
First, understand the way the loan process favors fakers. Real students need loan money to buy books and supplies at the beginning of the semester. So schools must advance at least some of the money blindly, with a fingers crossed mindset. Many pay out a portion then hold back the rest of the loan until later in the course and census day. Taking attendance and watching student activity carefully can provide some intel that may signal fraud but most schools don’t live in a Big Data world and can’t mine the data because of constraints on faculty and administrator time.
The fraud detection process badly needs to be automated. If schools are potentially losing 4% of Title IV funds, think what that means to a school that lends $100M, not an unusual amount for many schools. That’s big money schools stand to retain. If they only knew they could easily return this money to their budget if they simply watched the logins and authenticated the students with a high degree of accuracy.
Automated ID software can monitor all these elements for the tell-tale signs of fraud and send early warnings to administrators that will stop them sending out loan money until they can determine whether the student is truly authentic. It can run everything through a neural net – student attendance pattern, login location, history, activity, time – for anomalies that could never be detected by an individual or even a team dedicated to nothing else. There’s just too much data.
Step one is authenticating all students as they enroll. Authentication is different from simple identity checks at the LMS gate such as a username/password. That will not stop a dedicated fraudster. They could give their credentials to an accessory and have that person simply login at the appointed time the whole semester and pocket the whole loan! When schools use a biometric login like BioSig-ID, they know that the password students that draw with their finger or mouse can’t be given to anyone else. No one else can reproduce it.
If you tie the biometric password to an additional ID resource like a government ID check at registration (via webcam), then you’ve locked things up tightly. BioProof-ID is such a product – with respected proctor B Virtual handling the ID check then passing off to BioSig-ID.
Once BioSig-ID is in use, distance learning institutions will know exactly who their students are. But fraud and academic dishonesty protection is just getting started. The ability of software to crunch all the student activity data, sifting for pattern deviations, means any fraud signs will be instantly delivered to schools before loans go out. Schools then put their regular procedures in place, issuing warning letters or whatever action they decide to take.
This two prong approach is win-win. Especially when you factor in the ROI. How about recovering say, $400K, that you might have lost in fake loans….would a cost-effection solution that recovers it be worth it?
Do the math.