
Targeting Moroccan customers
Money transfer and foreign exchange provider UAE Exchange is partnering global payments provider Western Union to extend joint operations into Morocco (view press release). The aim of the new joint venture is to widen the availability of online and remote payment solutions to consumers in Morocco. UAE Exchange is already an agent for Western Union in the Middle East.
Mr Y. Sudhir Kumar Shetty, COO – Global Operations, UAE Exchange believes the partnership will benefit its many customers in the country. He said: “We are glad to extend the experience, expertise and convenience gained over the years to benefit our mutual customers in Morocco. This further adds to our vision of bringing more value to the beneficiaries of our customers. Both brands bring the best of integrity and quality to the table, which is good for the beneficiaries of our Moroccan customers.”
“Our focus has consistently been on increasing access whilst maintaining service excellence and we are confident that this is a goal we share with UAE Exchange,” added Aida Diarra, Senior Vice President, North, West and Central Africa at Western Union.
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