Swift Tests Use of AI to Fight Cross-Border Payment Fraud | PYMNTS.com

2025-09-15 13:50:33 英文原文

作者:PYMNTS

By  |  September 15, 2025

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Swift conducted tests to demonstrate the potential impact of artificial intelligence in preventing cross-border payments fraud.

The global messaging system collaborated with 13 banks on experiments using privacy-enhancing technologies (PETs) to let institutions securely share fraud insights across borders, according to a Monday (Sept. 15) press release.

In one instance, the PETs allowed participants to verify intelligence on suspicious accounts in real time, “a development which could speed up the time taken to identify complex international financial crime networks and avoid fraudulent transactions being executed,” the release said.

In another case, participants employed a combination of PETs and federated learning, or an AI model that “visits” institutions to train on their data locally and lets them work together without sharing customer information, to spot anomalous transactions, per the release.

Trained using synthetic data from 10 million artificial transactions, the model was twice as effective in identifying fraud than a model trained using a single institution’s dataset, the release said.

“These experiments demonstrate the convening power of Swift as a trusted cooperative at the heart of global finance,” Rachel Levi, head of AI for Swift, said in the release. “A united, industry-wide fraud defense will always be stronger than one put up by a single institution acting alone. The industry loses billions [of dollars] to fraud each year, but by enabling the secure sharing of intelligence across borders, we’re paving the way for this figure to be significantly reduced and allowing fraud to be stopped in a matter of minutes, not hours or days.”

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In the wake of these experiments, Swift plans to widen participation before beginning a second round of tests, which will use real transaction data in hopes of demonstrating the technologies’ effect on real-world fraud, the release said.

When it comes to preserving trust in financial transactions, sharing data is important.

“It’s a team sport,” Entersekt Chief Product Officer Pradheep Sampath told PYMNTS in August. “And the thread that binds us all together is data that’s actionable, shared in good faith, and governed responsibly.”

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摘要

Swift conducted tests with 13 banks using privacy-enhancing technologies (PETs) to share fraud insights securely across borders. The experiments included real-time verification of suspicious accounts and the use of federated learning for detecting anomalous transactions. Trained on synthetic data, the AI model showed twice the effectiveness in identifying fraud compared to a single institution's dataset. Swift aims to expand participation and conduct further tests with real transaction data to demonstrate practical impact on cross-border payment fraud prevention.