Maryland Man Uses Faux Pharrell Williams Concert to Rob South Korean Company of $375,000

Pharrell Williams was tied into a bit of international crime this week when a man was arrested for falsely accepting payments to organize a concert with the performer for Korean clients. The story only gets more comedic from there.

The FBI arrested Sigismond Segbefia of Silver Spring, MD, on charges of wire fraud, bank fraud and identity theft on Tuesday. The 28 year-old claimed to represent a company called Eastern Stars LLC, a front he used to communicate with Dosko Co. Ltd., a South Korean steel company that was looking to book Williams for a concert. The reason why the front was successful was because the company wasn't entirely a front...the defendant had actually incorporated Eastern Stars during 2013. His background work was impressive, except for the fact that it was all done illegally: Segbefia provided fake documents, e-mail addresses and the names of Williams' management team in order to make his claims more convincing.

Finally Dosko, believing that Segbefia was truly connected with a Japanese entertainment company, wired him $375,000 to book the show. They got suspicious the next day however and attempted to cancel the transfer, by which point Segbefia had already withdrew $113,000 from his bank account.

Dosko was reportedly aiming to branch out into entertainment to diversify its holdings. David Cho, the son of company president Sungdae Cho, was in charge of the new entertainment division. We'll see how long that lasts.

This wasn't Segbefia's first instance of fraud however. The FBI reports that he's allegedly stolen more than $445,000 from various women that he met on dating sites. The most he grabbed from one victim was a woman who sent him $185,000 over half a year, supposedly to help him get his medical equipment company off the ground. The cherry on top is that Segbefia committed all of these acts using the stolen identity of a Pennsylvania postal worker.

Tags
Pharrell Williams
Join the Discussion
Real Time Analytics