AML transaction monitoring
NETGUARDIANS
Monitor all transactions and meet regulatory AML requirements while reducing false alerts and operational costs.
A growing burden
An estimated 2-5% of global GDP is laundered every year. Methods of money laundering are constantly evolving, becoming more sophisticated, faster and difficult to detect.
International regulatory and oversight bodies such as the Financial Action Task Force (FATF) and the Basel Committee on Banking Supervision (BCBS) have continually highlighted the need for more robust AML controls in financial institutions, while regulators have responded with stricter regulation and heftier fines for control failures.
In a world of instant payments with ever-increasing transaction volumes, the detection problem is exacerbated.
Against this backdrop, effective transaction monitoring requires a combination of detecting potentially suspicious behaviour, investigating all resulting alerts and reporting suspicious activity – across your customer base you must be able to intelligently ‘know the good and spot the bad’. It is now time for a new approach and evolved techniques to address this growing transaction monitoring burden.
Vyntra’s Transaction Monitoring solution helps you accurately detect suspicious transactions whilst intelligently ensuring operational efficiency.
Key benefits
Core capabilities

Strengthen your AML controls with Vyntra’s Transaction Monitoring solution
Vyntra’s NG|Screener platform integrates internal and external data sources and analyzes these through rules and machine learning to accurately detect potentially suspicious behavior. It can monitor large volumes of transactions in batch or real-time, offering deeper insights, reducing false positives and improving operational efficiencies.
Recognitions
Vyntra was named a global leader in the 2021 Aite-Novarica report on Fraud and AML Machine Learning Platforms. It was ranked best in class for client strength and client service.
Banks that use Vyntra had reported to Aite-Novarica that the vendor was “very attentive, responsive and competitively priced” and that they were “very satisfied with the platform’s features and functions… [and] with the performance of the platform’s detection rates and accuracy.”
