Real-time Risk Detection

Implement a machine learning model in 10 steps — then evaluate, understand the drivers, and apply it to your data. Score transactions in real time, hand likely cases over to case management.

Risk detection systems need to be agile to adapt to changing realities, scalable to deal with increasing data volumes, and intelligent enough to detect increasingly sophisticated patterns and reduce false-positives.

An integrated case management tool captures all the inputs from historical and live data, surveillance analyst notes, and transaction log extracts to fully investigate the risk when an alert is raised.

Use cases include anti-money laundering, trade surveillance, credit/debit card monitoring, health insurance fraud, insurance fraud, and online operations.

Data discovery, machine learning model creation, and real-time deployment is accessible within a single tool to find risk patterns and set thresholds to model results.

Accelerate the adoption and rolling out of real time action with a graphical flow based development that reduces complexity and increases collaboration. Projects can span over multiple assets and data and scenarios, with connectivity to over 150 options.