lifecycle management of contactless applications
GlobalPlatform, an organisation which standardises the management of applications on secure chip technology, has updated its compliance programme, designed to ensure consistency in the lifecycle management of contactless applications. The company claims that certification of compliant products to this specification will give service providers the confidence that applications will perform as intended, regardless of the mobile handset being used.
Card Specification v2.2 Amendment C, also known as Contactless Services, defines the deployment and lifecycle management of contactless applications, where all necessary information about the contactless protocols is defined at the time of installation. A key feature of this specification is the consistent end user experience that is provided regardless of the user interface, which is generated by an OS application which can be tailored by the wallet issuer to meet their needs and those of the service provider.
Companies that have launched GlobalPlatform qualified test tools which verify that a UICC product meets the functional requirements outlined within the GlobalPlatform Card Specification v2.2 Amendment C include Barnes International, FIME, Galitt and Collis.
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
