Self Learning Optimisation

A Unique combination of AI-based Natural Language Processing and Machine Learning technology

The Challenge
With the increasing cost of compliance and heightened pressure from regulators globally, financial institutions are being forced to be more innovative in handling compliance in a demanding and dynamic market. Watchlist Screening is becoming ever more complex, with false positive rates increasing for many institutions. The amount of false positive alerts adds to the increase of cost an increased risk of human error.

The Solution
Leveraging the AI disciplines of Natural Language Processing (NLP) and Machine Learning (ML), Pelican Secure Self Learning Optimisation is a giant leap forward in the watchlist screening industry. It integrates with your existing watchlist screening solutions to drastically reduce false positives, cutting compliance cost and delivering reputational protection across all payment processes and counterparties while protecting your compliance investment.

 

Reduced false positives with your existing screening tool

Reduce Your Cost and Risk 

Using AI disciplines along with deep domain knowledge, the solution analyses operator’s actions to learn the human reasoning from solved alerts, thereby reducing false positives and presenting you with a model for approval, along with continuous and supervised learning. 

This decrease in the number of false positives reduces the cost to compliance as well as the risk of human error. 

Secure Self Learning Optimisation uses advanced technologies of NLP and Machine Learning that work with your existing third-party screening tools to protect your compliance investment.

Pelican Secure Self Learning Optimisation Features

  • Captures, analyses and learns from user actions and payments attributes
  • Ongoing supervised learning on how alerts are resolved
  • Full control by authorised users in configuring the engine logic, parameters or thresholds authorisations
  • Explainable and auditable actions
  • Extensive knowledge base library of rule-like understanding models to enable fine tuning of alert generation
  • Base decision-making models built on years of payments experience
  • High throughput and low latency

Pelican Secure Self Learning Optimisation Benefits

  • Works alongside your existing third-party Screening engine; improving the results and protecting your investment
  • Suitable for real-time payments schemes
  • Self Learning Optimisation mimics human decision-making process
  • False positives are reduced by 75% on average
  • Alerts can be reviewed and decisioned without manual intervention, typically resulting in 75% reduction in alerts within 6 months of deployment

Find Out More

Pelican Secure Brochures & Datasheets

Please use the Download button below to access the full library of Pelican Secure information resources, including datasheets covering Payments Fraud Detection, Offline and Real-Time AML Monitoring, Watchlist & Sanctions Screening and Trade Based Money Laundering Monitoring & Screening.

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