GURUGRAM: A woman, who lives in Sector 14, was cheated of Rs 72,000 by online fraudsters who allegedly offered her an SUV through a lucky draw.
The woman made an online purchase of some items on
shopclues.com and the product was delivered as promised. Then, after a few days, she got a call from someone who identified himself as an employee of shopclues.com and told her that she has won an SUV. He asked her to pay Rs 75,000 for its registration.
The complainant paid the amount, after which the number she received the call from was deactivated.
The complainant, Santosh Kumari, filed a complaint on July 6, 2018. After the initial investigation was completed, a case was registered on Sunday at Sector 14 police station.
“The caller told me the product I had bought came with a lucky draw offer, and that I have won a SUV on it. He congratulated me and said I will have to pay the registration fees for the vehicle to be delivered,” said Santosh in her complaint, adding that the caller asked her to transfer the money on a given number via Paytm.
But after she had transferred the amount, she found that the caller had switched off his mobile.
“Despite repeated attempts, when I failed to contact them, I realised I had become victim of a fraud,” Santosh explained. SI Raj Singh of Sector 14 police station said a case has been registered under sections 419 (cheating) and 420 (fraud) of IPC. “We’re trying to track down the caller,” said Singh.
In the first six months of 2018, the number of cases registered daily by the Gurugram cyber crime cell is 11. The total number of cases registered till June 20 was 1,728. Only in 23 of these cases have FIRs been registered, and none of the cases have been resolved.
Around 50% of complaints received by the cyber cell are related to banking frauds through phones.
In 2017, nine cases of cyber crime were registered every day. The total numbers of cases registered was 3,297, which included 1,916 for online banking frauds, 264 complaints pertaining to Facebook, 240 related to internet fraud and 51 related to data theft.