The concept of "face brushing" has become a trending topic, with facial recognition technology steadily entering the public spotlight. Apple’s new iPhone X introduced a "face brushing" unlocking feature that can be used for Apple Pay and various app authentications. A KFC restaurant in Hangzhou recently launched a commercial pilot for "face brushing" payments, while some banks are experimenting with automatic teller machines (ATMs) that allow users to withdraw cash by scanning their faces. High-speed rail ticket checks and hotel check-ins are also adopting this technology, marking a growing shift in how we interact with digital systems.
Facial recognition is now being applied across all aspects of daily life—clothing, food, housing, and transportation—signaling a period of rapid adoption. The financial and security sectors have been among the first to embrace it. As the number of commercial applications expands, the market potential is vast, and investors are taking notice. According to the Prospective Industry Research Institute, the Chinese face recognition market exceeded 1 billion yuan in 2016 and is expected to reach approximately 5.1 billion yuan by 2021.
The "Face Brushing" era is fast approaching as the technology matures. Industry experts believe that facial recognition is breaking through application barriers, creating increasingly diverse use cases. Yan Shuicheng, vice president of 360 and director of the Institute of Artificial Intelligence, notes that with the emergence of deep learning algorithms, the accuracy of facial recognition has significantly improved compared to five years ago. The data collected from various devices helps build large datasets, which serve as essential training material for these systems.
Chen Jidong, head of biometric technology at Ant Group, adds that recent advancements in deep learning have enabled machines to simulate human brain learning through neural networks. By using convolutional neural network models and massive image data, biometric accuracy has risen from around 70% or 80% to as high as 99.6% or even 99.7%. In payment scenarios, the misrecognition rate has dropped to one in 100,000.
Xie Yinan, Vice President of Technology, outlines three major application directions: 1:N authentication for identifying individuals within a group, such as in access control and security; 1:1 authentication for real-name verification, like airport boarding and station entry; and live body detection to ensure that a real person is performing an action, such as remote account authorization.
Facial recognition is gradually moving beyond traditional settings into areas like unmanned retail, quick payments, and hotel check-ins. This trend has attracted significant investment. For example, Shangtang Technology raised $410 million in Series B funding, while Yitu Technology and Cishi Technology completed Series C rounds of 380 million yuan and 100 million USD respectively.
In the financial sector, the adoption of facial recognition has grown rapidly. Companies like Ant Financial, JD.com, and Suning have launched "face brushing" payment features, while traditional banks such as China Merchants Bank are piloting similar technologies. Apple’s iPhone X, with its Face ID feature, has brought attention to the potential of facial recognition in secure transactions.
At a KFC in Hangzhou, customers can now pay using facial recognition. After selecting their meal on a kiosk, they choose "face payment" and undergo a quick scan. The process takes less than 10 seconds, making it faster and more convenient than traditional methods.
In urban security, facial recognition is proving invaluable. It can now handle comparisons involving over 10,000 people, helping law enforcement identify fugitives more efficiently. Shangtang Technology, for instance, has assisted police in solving thousands of cases and capturing hundreds of suspects.
Compared to fingerprint and iris recognition, facial recognition offers a non-contact advantage, improving system speed and user experience while reducing health risks associated with physical contact. Its "non-intrusive" nature also makes it ideal for public safety applications.
Beyond security and finance, facial recognition is becoming popular in entertainment. Smartphones now feature facial unlock functions, smart albums can sort photos by face, and apps like FACEU allow users to transform their images for social media interactions.
Looking ahead, experts predict that facial recognition will play a key role in smart homes, where doors open only for the owner, TVs recognize users and suggest content, and robots provide personalized services. Businesses may also use facial data to better understand customer behavior and tailor marketing strategies.
While the technology continues to improve, challenges remain. Experts warn that real-world conditions—such as lighting, angles, and makeup—can affect accuracy. However, many companies are working to enhance reliability and security. For instance, Apple uses a combination of infrared sensors and a secure enclave to protect face data, while Alipay employs 3D depth cameras and live detection to prevent fraud.
Privacy concerns are also a growing issue. Unlike fingerprints or irises, facial features are often visible in public, raising questions about data protection. Solutions include desensitizing images, encrypting data, and ensuring secure storage. Industry leaders emphasize the need for standardized protocols to safeguard user information.
As facial recognition becomes more integrated into daily life, the focus must shift toward balancing innovation with security and privacy. With continued improvements in accuracy, safety, and ethical guidelines, the future of facial recognition looks promising.
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