Global provider of tablet PCs and supporting mobility solutions, Motion Computing, and global electronic payments security technology developer, MagTek, are making QwickPAY, a secure mobile payment solution, available for the Motion CL900 SlateMate tablet, with Magnetic Stripe Reader and Barcode Scanner. QwickPAY will enable secure transaction processing from anywhere in the store via the CL900 SlateMate thus providing retailers with a mobile, end-to-end point-of-sale solution.
Transactions are processed via the CL900 SlateMate’s integrated Mag Tek Secure Card Reader Authenticator. Having swiped the card the customer signs using the CL900’s digitizer pen and payment is made. The vendor can also run standard or customised reports on the mobile platform.
Bill Rorick, MagTek vice president, commented of the technology: “By combining the secure payment functionalities of QwickPAY with the mobility and information collection capabilities of the Motion CL900 SlateMate, we’re creating a solution that benefits both retailers and their customers because it creates efficiency and speeds up the transaction process while still remaining absolutely secure.”
Whitepapers
Related reading
Central banks best suited to issue digital currencies
By Aaran Fronda A recent report by the Official Monetary and Financial Institutions Forum (OMFIF) said that central banks rather than private ... read more
Instant payments: innovations inbound for corporates
In 2020, instant payments look set to continue their current trajectory to become the biggest trend in payments. While these schemes already offer numerous benefits to corporates, leveraging innovations such as APIs and request to pay will go some way to unlocking their full potential, argues Michael Knetsch
Obstacles exist for banks to meet ECB’s instant payments goal
The cost of joining instant payment platforms will be one of many hurdles banks and payment services providers must overcome to meet ... read more
Banks must be aware of “biases” in data used to train ML models
Financial institutions need to be conscious of biases in the historical data that is being used to train machine learning (ML) models, ... read more
