touch and pay

Liquid, Inc., who conduct research and development of biometric authentication engines, will begin full-scale introduction in October 2017 of the next-generation fingerprint authentication system “Touch & Pay”, expanding nationwide for social implementation in 2020.

Together with full-scale introduction, they will hold a special member registration campaign for “Touch & Pay”, with winners receiving up to 1 million yen’s worth of points.

“Touch & Pay” is one of the “infrastructure improvement projects to create new business for IoT promotion” (IoT-based Omotenashi Demonstration Projects) promoted by the Ministry of Economy, Trade and Industry. It is a stress-free, next-generation platform that allows you to enjoy various payment services and hospitality services using fingerprint-based biometrics. With a view to social implementation in 2020, we have been conducting field trials at about 220 sightseeing and accommodation facilities in towns such as Yugawara and Hakone since 2016, and in October we will begin full-scale introduction of “Touch & Pay”, expanding to operating facilities all across Japan.

Changing future lifestyles with a next-generation fingerprint authentication system
“Touch & Pay” is a system that provides accurate and high-speed fingerprint authentication on tablets and fingerprint readers. Registering tickets or cash with fingerprints will reduce the need to worry about lost items and eliminate queues and congestion due to ticket processing. In addition, if it is linked with a credit card, etc., it is not necessary to remember a PIN number, and a “hands-free life” where you do not need to carry things, can be realized.

Technical features of Touch & Pay

  • Fingerprint feature points are digitized and encrypted, making restoration following data theft impossible
  • Fingerprints themselves are not stored as image data, and “feature points” such as endpoints and branch points are stored in a unique format. Even if the data is stolen, it is impossible to recreate the fingerprint image.
  • Achieving high accuracy with image analysis AI technology
  • By acquiring more feature points than general fingerprint authentication or vein authentication, we have achieved accuracy that is approximately 90,000 times (one in 9 billion) that of general fingerprint or vein authentication (the probability of mistaking another person for oneself).
  • Machine learning index search technology allows us to achieve high-speed authentication, even for large-scale use

Unlike the conventional sequential search of biometric authentication, we utilize a patented machine learning index search technology to realize a speed 300 times faster than the conventional type, when used on a large scale.