Financial institutions use a variety of methods and technologies to conduct sanction screening as part of their AML and CTF compliance programs. Some common approaches include:
- Manual screening: Financial institutions may manually screen customer names against various sanction lists using spreadsheets, databases, or other software. This approach can be time-consuming and error-prone, but may be suitable for smaller institutions with fewer customers.
- Automated screening: Many financial institutions use automated sanction screening software that can quickly scan large volumes of customer data and match it against sanction lists. These tools use algorithms and artificial intelligence to identify potential matches and reduce false positives. Examples of automated screening tools include software from vendors like Accuity, Refinitiv, and Dow Jones.
- Watchlist filtering: Some financial institutions use watchlist filtering to flag suspicious transactions based on predefined criteria. For example, a transaction that involves a customer on a sanctions list or a high-risk country may be flagged for further review. Watchlist filtering can be an effective way to reduce the number of false positives generated by automated screening.
- Machine learning: Some financial institutions are beginning to use machine learning algorithms to improve the accuracy of sanction screening. These algorithms can learn from previous screening results and adapt to new patterns and threats over time, improving the institution’s ability to detect and prevent financial crime.
With Fastcheck, you can streamline your sanction screening process and avoid the risk of violating regulatory compliance. Our advanced technology can quickly and accurately check your customers against multiple sanction lists, reducing false positives and saving you valuable time. Take action now and sign up for Fastcheck! Contact our team to schedule a demo and see how our platform can transform your sanction screening process.
