
Available to merchants regardless of country
European e-payments processor, Failsafe Payments, is expanding its CertoPay solution to online merchants resident in countries where businesses acquiring banks evaluate on risks scale as low and medium risk (view press release). CertoPay allows merchants to implement the acceptance of electronic payments on their websites. The solution had initially been available for merchants with all types of business but registered only in the Visa EU area and MasterCard SEPA. Internet merchants, regardless of country of registration, will now be able to accept payments on their websites and use all features and services that CertoPay provides.
“Today we have very good conditions for provision of processing services to the merchants with low and medium risk business, registered in any jurisdiction in the world, including offshore zones. As for clients whose business acquirers refer to high risk, only merchants’ residents of Visa EU area and MasterCard SEPA can get connected to CertoPay processing platform,” said Alexander Mihailovski, MD of Failsafe Payments East Europe.
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