Former NY state employee admits to identity theft, abusing IT access

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Chris Teale By Chris Teale,
Managing Editor, Route Fifty
 

Connecting state and local government leaders

By Chris Teale

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The employee pleaded guilty to creating and approving false unemployment insurance applications, including for pandemic relief, by using his state computer access.

A former employee of the New York State Department of Labor (NYSDOL) pleaded guilty to mail fraud and aggravated identity theft after he admitted to abusing state computer systems to create and approve false unemployment insurance claims.

Wendell Giles, 52, admitted to abusing his access to state computer systems alongside a colleague at NYSDOL, Carl DiVeglia, for the false claims in 2020 and 2021, which included applications for the federal Pandemic Unemployment Assistance program.

The U.S. Attorney’s Office in the Northern District of New York, which announced the guilty plea alongside representatives from the FBI and the U.S. Department of Labor’s Office of Inspector General (USDOL-OIG), said Giles recruited relatives, friends and friends-of-friends and instructed them to submit false claims to DiVeglia by phone.

The pair then took a share of the benefits NYSDOL paid out. Prosecutors said Giles used the money he fraudulently acquired to enrich himself.

Giles admitted to being responsible for more than $825,000 in losses from pandemic-related unemployment assistance administered by the state and agreed to pay full restitution to NYSDOL. DiVeglia had already pleaded guilty to related charges and agreed to pay restitution.

Giles could receive a 20-year prison sentence for his mail fraud conviction, a fine of up to $250,000 and supervised release of up to three years. The crime of aggravated theft has a mandatory sentence of two years in prison, which would be imposed consecutively to any other prison sentence. He is scheduled to be sentenced on Jan. 5, 2023.

The FBI and the USDOL-OIG investigated the case, assisted by the NYSDOL Office of Special Investigations.

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