Man arrested after 23,000 bogus customer service scam calls in over a week
Hong Kong police have arrested a 24-year-old man over an alleged scam operation that made more than 23,000 fraudulent calls in over a week by impersonating e-commerce customer service representatives, with one victim losing more than HK$100,000 (US$12,741). The force said on Sunday that the man was suspected of operating a call centre for a syndicate that posed as online shopping platform staff…
Police in Hong Kong have apprehended a 24-year-old man for allegedly orchestrating a scam that resulted in over 23,000 fraudulent calls over the course of a week. The suspect is accused of impersonating customer service representatives from online shopping platforms to trick victims into transferring money under false pretenses.
According to Senior Inspector Liu Long-kwan of the Commercial Crime Bureau, the criminal group posed as staff from e-commerce companies, claiming issues with purchased goods or threatening annual fees to extort funds. Police conducted a raid on a Tseung Kwan O residential flat on Friday and arrested the man on suspicion of fraud, seizing numerous SIM cards, a modem-pool device, mobile phones, a computer, and a tablet.
Investigators believe the man utilized the flat as a central hub for the fraudulent calls and registered a significant number of SIM cards under a fictitious company name. The modem-pool device, capable of making over 23,000 automated calls over the past week, was controlled remotely via a software program installed on a seized computer.
One of the linked SIM cards corresponds to a recent case where a victim lost more than HK$100,000 (US$12,741). The arrested individual is currently being held for further investigation. Authorities advise the public to verify the identity of callers and exercise caution when asked for money, warning that selling SIM cards registered to one's name could lead to criminal liability if misused for fraud.
Written by urgent.news from South China Morning Post's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
