Memory at an affordable price
The new tag, called the MicroPass 4101-2K, is claimed by INSIDE Secure to be the first NFC Forum tag that provides sufficient memory for demanding applications at an affordable price (view press release). The tag is based on the MicroPass contactless payment platform and is compliant with NFC Forum Type 4 tag requirements, with 2K bytes of memory to store application data such as URLs, business cards, phone numbers, wifi and Bluetooth pairing information.
Bernard Vian, executive vice president of NFC and Payment Solutions at INSIDE Secure says, “Until now, application developers have faced the dilemma of either paying too much for a true NFC Forum tag with enough memory for their applications, or using a more cost-effective but proprietary solution based on MIFARE Classic technology that presents interoperability issues…The MicroPass 4101-2K solves this dilemma by providing developers with a compliant NFC Forum Type 4 tag that has sufficient memory at an affordable price and that can be read by any NFC device.”
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
