Payment service provider Paymill has secured an additional funding of Blumberg Capital, bringing the total capital raised between Blumberg, Sunstone and Holzbrinck well over EUR10m. Paymill facilitates implementation of online credit card payment and other payment procedures in their customers’ online shop platforms.
Mark Henkel, CEO of Paymill: “The strong investment support from Holtzbrinck Ventures, Sunstone Capital emphasised our strong position as a technology leader in the European online payment market. With the latest investment of Blumberg Capital we want to make another step forward and continue our mission in optimizing our technical platform and our customer service. It’s our goal that everyone globally can accept online payments fast and easily.”
“This is an exceptional team going aggressively after an underserved market globally, and we are excited to be part of the team,” said Jon Soberg, Managing Director at Blumberg Capital.
Integration of the service is facilitated for merchants by simple copying and pasting of a few lines of code into the source code of their websites. The service includes providing of payment methods and secure payment processing in the background.
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