Rules-based transaction monitoring systems have several limitations and challenges, which have historically hindered their effectiveness in detecting and preventing integrity risks.
For example, the rules and thresholds need to be manually created and updated, making the system less adaptable to evolving and emerging threats. Similarly, rules-based systems also typically analyze individual transactions in isolation and may not provide a comprehensive view of supplier relationships.
In contrast, by combining multiple internal and external data sets all at once, Contextual Monitoring transforms the view of risk to a gain clearer understanding of multi-tier supply chains, their relationships and behaviors in real time. Using advanced entity resolution and network generation techniques, Contextual Monitoring focuses on holistic relationships rather than transaction risk in isolation.
This added context helps to identify hidden risk and generates fewer, more accurate alerts. Institutions can reduce rising compliance and operational costs and conduct more effective and efficient intelligence-driven risk processes without replacing existing systems.