Alipay and WeChat’s facial payment devices have landed around 100,000 units, and cloud flash payment has also been launched in seven cities including Guangzhou and Hangzhou. In terms of the number of installations, the overall landing effect of the facial recognition device is ideal. Now merchants have a strong dependence on the use of QR code payment services, and they are worried that facial recognition will encounter unnecessary troubles due to technical and ethical issues.
The opportunity cost borne by merchants will be increased from the conversion of QR code payment services to facial payment services. Therefore, the next competition around the merchants may extend from the level of subsidies to the level of concessions. More importantly, in addition to the current supermarkets, convenience stores, hospitals, etc., which have become the first places to put face-brushing equipment, schools, enterprises, and public transportation will become ideal landing scenes for face-brushing equipment. The immediate business prospects of payment providers are immeasurable. According to the report of the Prospective Industry Research Institute, the face recognition market will maintain an average annual growth rate of 25% in the next 5 years, and it will reach approximately 6.7 billion yuan in 2022. Face-swiping payment, smart medical care, smart campus, smart bank, catering, supermarket, hotel, non-sense parking lot, various scene solutions, software customization development, payment equipment wholesale, please Baidu "Zhangyou Electronic Wei" for details
However, for face payment service providers, the market voice of success or failure is ultimately in the hands of users. Therefore, when subsidizing B-end merchants, Alipay and WeChat have also transferred part of their firepower to C-end consumers. On the one hand, Alipay provides various discounts for users who pay with their faces through the "8.8 Scanning Festival", and on the other is WeChat’s "face-scanning to receive red envelopes" assassin. WeChat even sent members of the face-paying team to merchant stores. Be a cashier and obtain KPI data from it; not only that, whether it is "WeChat Frog pro" or "Dragonfly Plus", you can provide users with a "face-to-member" solution, which completely connects face payment and card membership , The conversion channel of code members.
The use of non-sensible facial recognition payment should be an upgrade of the payment experience for consumers. In addition to not having to carry cash or bank cards during the consumption process, users can also get rid of the dependence on the mobile phone medium. Therefore, in general, the face-to-face payment is a payment change completely separated from the physical carrier medium; in addition, when the mobile phone is forgotten or lost Consumers can still complete transactions by swiping their faces in many special scenarios, such as mobile phones without electricity or network disconnection, large bags of heavy luggage items, etc., and swiping faces can also shorten the payment waiting and payment time for consumers, and the consumption experience is convenient Greatly improved; not only that, face payment can also provide the most direct convenience for special groups such as the elderly, deaf, blind, etc., so as to better promote the implementation of inclusive finance.
However, while the public is reaping the convenience and pleasure of consumption, they also question the safety and risk of facial payment. Compared with fingerprints, iris, etc., human faces have biological characteristics of weak privacy, and because of the lack of mobile phones as a medium, the “cloning” and utilization of face information will become easier. Accordingly, users use The risk of paying by face is even higher.
The basic principle of facial payment is to compare the information collected by the terminal hardware with the information stored in the cloud to see if the information is consistent, and then unlock to complete the facial payment. This may bring three risks: one is information leakage in the cloud biodatabase, which is acquired and mastered by criminals, resulting in "face theft"; the other is the use of photos, masks and other prostheses to attack users’ funds Cause harm; third, the algorithmic loopholes that may be hidden or newly added are discovered and used by criminals, thereby causing systemic risks.