Worldline Sanction Screening

03 / 11 / 2023

Sanction screening against official and customized sanctions lists. Data monitoring and optimized matching - all in real time.

Sanction Screening

To fight against the financing of terrorism (CFT), banks and other financial institutions cannot keep up with changing market behavior and regulatory updates. This results in high false positives* that burden your compliance teams with non-value adding work. With industry new normals, such as instant payments, growing businesses need modern solutions that meet changing regulatory requirements and keep teams efficient and effective.

Combining classic Embargo and Wire Transfer Regulation checks with Machine Learning across all payment types, the Worldline Sanction Screening solution speeds up your investigations and reduces unnecessary workload on your compliance teams. False positives can be reduced by up to 70% through autoclosing based on customer context and behavior, as well as previous & ongoing case decisioning. Seamlessly integrated into the Worldline Payment back office processing product suite or offered as a stand-alone service, discover the benefits of our leading FinCrime surveillance platform.

Your key sanction screening questions, answered

  • Following lists are covered as part of the standard solution: OFAC Lists (SDN, Consolidated), GB Financial Sanction List (HM Treasury List), UN Financial Sanction List, EU Financial Sanction List and the new EU Consolidated Financial Sanction List.

    Through our partners we can cover optionally a wide variety of additional lists from all around the world including, but not limited to, Personally Exposed Persons (PEP), Relatives and Closed Associates (RCA), Watch-/Blacklist, and High Risk Country Lists.

  • Client-specific lists can be uploaded as CSV files, and they can easily be downloaded again. The lists can be modified or deleted at any time.

  • Our matching logic is based on a fuzzy matching approach established with proven algorithms (Levenshtein) and best-in-class tools (Elasticsearch). Before performing the name lookup, several hygiene and normalization steps are executed to address common data quality issues. 

  • False Positive Reduction machine learning models intelligently identify false positives generated by the rules engine and auto-close these, but retrospective review is enabled in a separate case queue if required.

    We continuously learn from past and ongoing case investigations and the respective human decision alongside these. Using supervised machine learning, we predict whether a new hit might be a false positive. 

  • Our solution is fully auditable and fully compliant with data protection/residency regulations such as GDPR, as well as information security standards such as IS27001. SOC/2 is currently planned.

  • Pre-configured rulesets coupled with our implementation experience and expert capabilities enable you to go live within a few weeks (depending on your requirements).