The expansion of global watchlists and a tightening regulatory framework creates many challenges for organisations. The need to rapidly adhere to regulatory directives and updated watchlists across all business lines and territories can be burdensome and complex, with serious financial and reputational consequences for non-compliance. The adoption of Open Banking and instant payment schemes presents further screening complexity. The amount of false positive alerts adds to the challenge as it increases the cost of compliance and increases the risk of human error.
Leveraging the AI disciplines of Natural Language Processing (NLP) and Machine Learning, Pelican Secure Screening is a market-leading financial crime compliance solution for Enterprise Watchlist and Sanctions Screening. It delivers reputational protection across all payment processes and counterparties and is deployed on both a local and global basis by multiple large and small financial institutions to ensure risk mitigation and reduce cost to compliance.
80% reduction in review times
Clients have seen increased compliance efficiencies thanks to our detailed alert reports.
Higher accuracy to mitigate human error risks
AI-powered automation ensures lower human intervention and consequent errors.
Continually increase accuracy and reduce false positives
Through AI, Machine Learning technologies and self-evaluation and feedback.
How it works
Improve detection and increase efficiency
Powered by AI, our real-time watchlist and sanctions screening solution improves detection and increases efficiency without sacrificing regulatory compliance. The result? It provides 100% accuracy with a very low false positive rate (FPR) - reducing review times by 80% and improving compliance.
It screens any type of real-time/instant payments - including RTGS, ACH, SEPA, real-time - and is format-agnostic supporting SWIFT, ISO20022, EDI, email, trade documents, and any other file or message type as well as customer base screening against any watchlists including sanctions and embargo lists.
- 40 + built-in matching algorithms and expert rules along with a highly configurable rules engine containing variable parameters to manage false hits
- Format agnostic - supports any network, file, or message type including unstructured and free format text
- Suitable for real-time payment schemes - high throughput / low latency through memory-based processing
- Self-Learning add-on - using advanced technologies, it understands and learns from human actions to minimise false positives
Screening and AI optimisation
Natural language processing and Machine Learning for accurate detection, low false positives, and higher STP.
Screening names during onboarding of customers and continuous customer-base screening.
Real-time and batch mode screening of any domestic or cross border transaction.
Flexible screening and workflow
Intuitive and configurable user interface, customisable workflow and alert management.
Compliance with FATF 16 (EU 2015/847), adverse media and stripping detection.
List and format management
Screening any format/message standard against sanctions, PEPs, adverse media and other custom lists.
Effective risk management
Avoiding reputational risk, fines and penalties with higher screening accuracy, reducing human intervention and consequent errors.
Screening all formats/message standards against any lists in one or multiple jurisdictions.
Lower false positives and 80% reduction in review times due to detailed alert information.
For further reduction in false positives rate through mimicking human decision-making process.
Easy integration with your payments systems and with Pelican Payments and Pelican Open Banking solutions.
Highly configurable user interface, workflow and alert management.
Find Out More
Built for simplicity and scalability, you can integrate Pelican in as little as four weeks. Reach out and our global team will help you find the right solution for your business.
Related resources & information
Solutions: Compliance integration. Comprehensive corporate financial crime compliance.Learn More >