
Mastercard has been forced to concede to a European Union ban on unregulated cross-border card fees after a seven year court battle.
In 2007 the European Commission declared that the multilateral interchange fees applied by MasterCard on cross-border card payments were contrary to competition law. Since then, Mastercard has capped fees for cross-border transactions within Europe at 0.2 percent for debit cards and 0.3 percent for credit cards.
In the most recent ruling, the Court of Justice of the European Union confirmed the decision made by the lower, General Court in 2012 to abide by the European Commission’s initial condemnation of Mastercard’s fees.
Disappointed with the results, Mastercard President Javier Perez said: “We will continue to comply with the decision as we have been doing for a number of years. This means we would maintain our European cross-border consumer interchange fees at a weighted average of 0.2 percent for debit and 0.3 percent for credit.”
The ruling only applies to Mastercard, but may prompt competitors, lawmakers and national regulators to examine the fees charged for card payments, prompting a broader regulatory drive to cut the cost of using payment cards.
Source: Reuters
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