Monday, 2023 September 25

Chinese AI unicorn Megvii cleared for USD 500 million Hong Kong IPO despite blacklist concerns

Chinese facial recognition startup Megvii’s application for a USD 500 million Hong Kong initial public offering (IPO) was cleared by the city’s stock exchange, which means that the firm’s expected IPO appears to be back on track, as reported by Reuters on Monday citing two sources with direct knowledge of this matter.

Megvii decided to postpone its Hong Kong listing in November when the city’s stock exchange asked the company to provide additional information, after the startup was put on a banned trade list by the US in October, together with seven other Chinese firms.

Megvii will file the updated listing information to the city’s stock exchange shortly after obtaining the clearance, an anonymous source told Reuters. The timetable has not been put in place, but sources said the company would file the updated prospectus after the Chinese New Year holidays, which starts from January 25.

The facial recognition developer filed its Hong Kong listing application on August 25, and according to the rules of the stock exchange, the firm would have six months from that date to start listing, with a maximum three-month extension time.

Megvii’s collected USD 750 million in its latest funding round in May from investors including Bank of China, the Industrial and Commercial Bank of China, a subsidiary of the Abu Dhabi Investment Authority, as well as Macquarie Group, reaching a valuation of USD 4 billion.

Founded in 2011, Megvii made RMB 949 million (USD 133 million) in total revenue in the first six months of this year, compared to RMB 305.8 million in the same period in 2018, according to the company’s previous prospectus. It booked RMB 5.2 billion in net losses in the first half of 2019, widening from RMB 728.9 million in the same period of 2018.

Technology from the company’s facial recognition open platform Face++ is already being used in several popular apps, including Alipay and Didi, according to the MIT Technology Review.


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