
Partnership with Zuora
Flexera Software has announced a partnership with Zuora, the subscription commerce, billing, and finance provider.
The partnership will enable application producers leveraging Flexera Software’s recently announced compliance management solution, which supports usage-based, trust-but-verify software licensing models, to automate customer billing through integration with Z-Business, Zuora’s leading subscription management platform. The integration is designed to provide the missing link in usage-based billing environments so application providers can automate the verification, billing and accounting of customer usage.
With Z-Business, producers can take online orders and process credit cards with PCI compliance via leading payment gateways, right from their applications.
Mathieu Baissac, Vice President of Product management at Flexera Software said: “Our combined solutions will allow our customers to offer turnkey, usage-based billing services for their software.”
“Teaming with Flexera Software, means more application producers can shift their business faster to the subscription economy,” said Brian Bell, Zuora CMO.
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