SheerID goes global with its automated student verification

Automated verification service SheerID has announced that its instant student verification is available in 191 countries, beating their competitors to offer that automation on such a wide scale.

SheerID provides automated verification for careers and lifestyles that can receive discounts, such as college students, teachers, first responders, or military service members who can get online price reductions or exclusive offers.

Last week, the Portland, Oregon-based company announced that its instant student verification, which had been available in about five dozen countries, is now available virtually worldwide in 191 countries. SheerID said this represents the first worldwide automated student verification for college and university students.

Nearly 9000 data sources

CMO Sai Koppala told ClickZ that a website with a student discount will ask for the student’s name, college or university and date of birth for verification. Client companies include Amazon, Lowe’s, Spotify and T-Mobile.

SheerID then checks that information through nearly 9000 authoritative data sources, either through an arrangement with the registrar of that school, or through an aggregator of such info.

Koppala says his company is the only one offering automated student verification on a wide scale, and that the two nearest competitors – Unidays and Student Beans – require that students first set up verified accounts.

New anti-fraud measures

Additionally, SheerID also announced two new anti-fraud measures.

When a student submits an email address, SheerID now verifies through a partnership with White Pages Pro that the email belongs to that student. Koppala said that this is accomplished by White Pages’ matching of various data sets to confirm that this email address has been previously used by this person.

SheerID said that traditional methods of verifying student emails, including ones used by SheerID, simply verified that the college or other email domain was valid and could result in fraud rates as high as 35%.

The other new anti-fraud measure is the use of machine learning-based pattern matching to better detect the authenticity of student documents that may be uploaded as part of some kinds of verification.

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