Prepared by Alyssa Levitz and the Unemployment Insurance Modernization team at US Digital Response, including Waldo Jaquith and Michael Smedberg. Last updated: May 4, 2021
Most existing fraud detection in unemployment insurance (UI) systems has been aimed at identifying the claimants who are trying to claim more in benefits than they are owed, e.g., by misrepresenting their wages. Detection relied on cross-referencing the claimant-supplied information with data from their former employer(s) with government databases like departments of motor vehicles or the Social Security Administration. If any discrepancies are found, manual intervention is required.
These existing detection practices are insufficient in the face of the kind of fraud that has skyrocketed since the passage and implementation of the CARES Act in Spring 2020: identity theft.
Criminals are using stolen identities (Name, DOB, SSN, and sometimes Driver’s License ID) and using that to apply for unemployment insurance before the “rightful claimant” (i.e., the real-world person attached to the applicant’s identity) can. In this case, the identity attached to the claim is a real identity — but it is not the same as the identity of the person applying and, down the line, receiving the benefits (i.e., the applicant is a “fraudulent claimant”).
Given the changing threat model of UI fraud, quickly delivering benefits to rightful claimants with less manual intervention requires updating systems to automatically do the following:
Scan the backlog for applications that clearly are or are not fraudulent; and
Confirm that a new applicant is presenting an identity that is unique, valid, and entitled to benefits, and is themself the rightful claimant.
Confirm that the person with an existing claim who changes personal information (e.g., bank account numbers) is the same person as the rightful claimant
USDR has researched companies that provide automated identity proofing services to help in these scenarios and taken the first pass at evaluating their solutions, government compatibility, and credibility. Below is a comparison of such vendors; this list is not comprehensive, but it includes the major players and some promising start-ups. When it comes to identity proofing for workforce agencies, solutions may need to be integrated together to make a comprehensive plan. Other services may be needed for a specific use case. If you need help or advice evaluating or implementing any of these solutions, please contact USDR.
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