Parth Desai, founder and CEO of Pelican

Pelican, a developer of AI-powered payments and compliance systems for banks, has launched a self-learning module that it said is capable of delivering significant reductions in false positive rates in alerts systems.
It said Pelican Sanctions Self-Learning can be deployed as part of its watchlist filter product, or can operate with any existing third-party sanctions screening application.
Pelican said the new module leverages AI, ML and Natural Language Processing technology to screen accurately against any standard or proprietary watchlist. The extensive tuned knowledge base can deliver significant FPR reductions, it claimed. Combining the AI disciplines together with deep compliance domain knowledge, Pelican technology said it can capture, analyse and learn from operator actions to automate the creation of new models, delivering further improved FPR reductions over time of up to 72%.
“Pelican Sanctions Self-Learning is a giant leap forward in the sanctions screening industry and is a powerful tool enabling financial institutions to reduce the number of alerts, while maintaining complete control and a full audit trail,” said Parth Desai, founder and CEO of Pelican. “In today’s environment of fluid and complex global financial crime compliance obligations, Pelican Sanctions Self-Learning can drastically cut compliance costs, whilst delivering reputational protection across all payment processes and counterparties. We are already working to extend the self-learning functionality beyond sanctions filtering to AML transaction monitoring and fraud prevention.”

by Guy Matthews