Swift debuts pre-validation service to cut cross-border payment delays

In a move it says will cut friction in cross-border payments, Swift is launching a real-time validation service for banks to check and confirm payee details related to the payment beneficiary prior to moving the transaction.

The Payment Pre-validation service enables banks to verify payee account details before an international payment is sent to cut down on failed payments or lost time because of incorrect beneficiary information — from misspelled names to transposed account numbers.

“Swift’s strategy to enable fast and frictionless payments takes a major step forward with the launch of this service,” Stephen Gilderdale, chief product officer at Swift, said in a Thursday press release. “Payment Pre-validation will bring end-to-end efficiency, enabling our customers to provide better, faster and new services to their own end clients.”

The new process allows a sending bank to confirm account details, via an API, with the receiving bank from the very beginning of the process so that any data or account problems are identified. The process is similar to what already occurs in some domestic markets, except Swift says its service will go much further — solving the issue for up to 11,000 institutions and 4 billion accounts in 200 countries.

Swift developed the service after working with a number of major global banks that have already committed to using the Payment Pre-validation. The new process is expected to have a major role in Swift’s ongoing development of an instant payment platform.

“Pre-validation is an important step in helping corporates to make simpler, faster and more secure cross-border payments,” Thomas Halpin, global head of payments product management at HSBC, said in the release. “This feature will ensure customers can send payments in confidence, and the increased security brings benefits not just for customers but for the entire payments community.”

Swift intends to improve the service in the coming months by offering additional checks based on reference data from millions of transactions to further predict, at the point of initiation, when a transaction may potentially run into friction points.

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