
One-stop shop
Invapay, a payment aggregator and trading platform has signed an agreement with cross-border payments service provider, Earthport, to use its payment platform to provide an end-to-end solution designed to enable a ‘one-stop shop’ for international supplier payments offering greater efficiencies and cost savings (view press release). Invapay, a regulated provider of procurement and electronic payment services wanted a service provider to help settle cross-border payments without having to develop individual relationships with banks overseas.
“Integrating Earthport will automate Invapay’s solution for international payments for the whole of the international supply chain, from big wholesale suppliers to the smallest one-time-only vendors,” said Sid Vasili, CEO and Founder of Invapay. “One-time-only vendors can account for 80% of an organisation’s purchase-to-pay administrative costs. This service will eliminate the need for manual payment processing and reconciliation for international payments, allowing us to reduce the cost for payment settlement.”
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