Suspicious settlements and anomalies happen in every complex network – shipping and logistics, communications, and finance. Applying network analytics to these transactions allows the business analyst to quickly identify anomalies and new suspicious patterns and provides them the tools to assess significance and impact.
- Difficult to identify the “signal” from the “noise” in large complex data sets.
- A single data set may not provide enough information to identify anomalies.
- A single static view provides limited resolution of emerging situations.
- On the fly filtering enables the proper focus to efficiently identify anomalous behaviours for deeper investigation from massive and dynamic datasets.
- Multiple datasets can be quickly and easily aggregated to provide a holistic view.
- Time series investigation provides trends and behavioural norms.