According to Finextra, at the latest economic and financial affairs meeting, the Council voiced their backing for the Single European Payments Area (SEPA) project and issued a reminder about the fast approaching migration deadline for Direct Debits and Direct Credit.
The Council expressed concerns over stakeholders that seem to be leaving their SEPA migration until the last minute, which could expose them to “undue operational risks impacting smooth handling of payments”. A recent report from the ECB exposed the issues hindering small and medium-sized enterprises (SMEs) and public authorities. The Council commented on the level of awareness calling the programme “fragmented and the level of preparedness is rather poor”.
A spokesperson from SmartDebit commented: “To be able to collect Direct Debit payments across Europe presents a great opportunity, not only to us but to our clients as well. Stakeholders should have an understanding of their clients and suppliers readiness as well as pressing forward with their own preparations. We are continuing our developments towards becoming SEPA compliant, and anticipate to have completed migration and full testing by the end of Q4 2013.”
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