Flywire, a US-based payment and receivables solutions provider, has enhanced its cross-border payment and receivables platform by adding new machine learning capabilities to it.
The addition of new capability is expected to improve the payment-to-settlement time, bolster security, and slash costs for payers as well as receivers.
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It will mechanise and simplify reconciliation of the number of international payments coming from different countries in different currencies, the company said.
Globally, financial companies can purge up to 20% of costs through the implementation of the technology while also improving service quality, according to research advisory firm Autonomous NEXT.
Rigid, rules-based systems are applied by typical legacy payment platforms to perform reconciliation of invoices with monies received. Hence, a significant manual effort is need to evaluate transaction records and reconcile payments.
The addition of machine learning-enabled deep neural networks and reinforcement learning techniques will augment the platform’s ability to streamline the identification and reconciliation of cross-border payments in real-time.
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By GlobalDataThe company claims that its platform is now able to automate the matching of more than 90% of cross-border transactions.
The addition of machine learning capabilities are expected to further optimise FX conversion.
Flywire VP of product Jason Moens said: “Accepting payments across borders is a highly complex process that increases the cost of collecting monies, opens up FX and fraud risks, and requires enormous operational investment.
“The addition of advanced machine learning further streamlines our clients’ payment and receivable operations and removes more of the potential risks that can negatively impact fundamental parts of their business. This allows them to offer customised payment solutions to more of their customers — wherever they are in the world.”
