BNY Mellon is implementing the Pelican Secure Sanctions Self-Learning Optimization™ (SSLO) solution to drive efficiency in its global sanction screening capabilities.
Pelican AI, a global provider of artificial Intelligence-powered payments and financial crime compliance solutions, was successful in a competitive proof of concept to reduce false positives that require time-consuming investigations by operations staff.
Pelican Secure SSLO employs AI technologies to analyse transactions flagged for investigation by the bank’s existing sanction screening tools. Machine learning (ML) and natural language processing (NLP) are deployed to understand and interpret human actions, helping to classify and explain the false positives generated, allowing the bank’s compliance operation to resolve false positives much more quickly.
According to Matthew Wells, head of global markets, issuer services and treasury services operations at BNY Mellon, the aim is to improve operational efficiencies without compromising regulatory needs.
“This solution provides full control in this critically important part of the payments value chain,” he said. “We believe that this is the start of a long-term relationship with Pelican and look forward to working closely to optimise our operations in the area of sanctions screening and payments.”
Pelican SSLO is designed to integrate with and complement existing sanctions screening tools to reduce the time taken to process false positives from existing compliance systems. “The system is able to continuously learn and maintains high levels of false positive reduction,” said Parth Desai, founder and CEO of Pelican AI.