Global Payments

Flywire Boosts Platform Capabilities With Machine Learning

Flywire Upgrades Payments With Machine Learning

Payment solutions company Flywire has added machine learning capabilities to its cross-border payment and receivables platform, according to a release from the company.

“The enhancements improve the payment-to-settlement time, increase security and reduce costs for both payers and receivers by further automating and streamlining reconciliation of the growing number of international payments coming from different countries in different currencies,” the company said.

According to research advisory firm Autonomous NEXT, machine learning technology can eliminate up to 20 percent of costs while simultaneously improving service quality.

“Typical legacy payment platforms employ rigid, rules-based systems to perform ‘best effort’ reconciliation of invoices with monies received for businesses and institutions collecting payments,” the company said. “These platforms are limited in their ability to support the ever-evolving business requirements, multiple currencies and myriad payment methods involved in collecting cross-border transactions. As a result, a significant manual effort is required to review transaction records and reconcile payments.”

Flywire said that with the addition of machine learning, the company has improved its ability to identify and facilitate cross-border payments in real time. Also, it can now automate 90 percent or more of those transactions, and the model will improve as time goes on.

“Furthermore, the machine learning algorithms require minimal supervision to learn and support new payment methods and can confirm payment sources, detect anomalous payments and escalate these to Flywire’s compliance and operations teams for review. The new capabilities also further optimize FX conversion,” the company said.

Jason Moens, VP of product at Flywire, said the new technology opens up a lot of opportunities for the company.

“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,” Moens said. “As more and more businesses and institutions leverage our platform to address these challenges, we continue to look for new ways to enhance its capabilities. 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 customized payment solutions to more of their customers – wherever they are in the world.”



About: Accelerating The Real-Time Payments Demand Curve:What Banks Need To Know About What Consumers Want And Need, PYMNTS  examines consumers’ understanding of real-time payments and the methods they use for different types of payments. The report explores consumers’ interest in real-time payments and their willingness to switch to financial institutions that offer such capabilities.