What is SAS Financial Crimes Analytics?
SAS Financial Crimes Analytics is an analytics solution that helps financial institutions detect and investigate financial crime risks using AI, machine learning, entity resolution, pattern matching and network analytics. It provides a holistic view of financial crime risk to help organizations identify anomalies, uncover hidden relationships and prioritize potential threats.
How SAS Financial Crime Analytics works
Get to know SAS Financial Crime Analytics
Key features
Easy data exploration & visualization
Lets you easily import your own data, build and run transformations, and augment and join data within an integrated visual pipeline of activities with a simple drag-and-drop interface.
Quick operationalization of analytical models
Operationalizes models quickly using automated techniques in just a few clicks – in batch and real time. A repeatable framework enables easy registration, validation, tracking, monitoring and retraining of analytical models to ensure they’re performing well.
Seamless integration
Uses advanced data management and powerful in-memory capabilities to integrate with your existing transaction monitoring platform. Works with your existing AML solutions, so there's no need to replace your current platform.
Easy-to-use analytics
Lets you visually explore and evaluate segments for further analysis using k-means clustering, scatter plots and detailed summary statistics. Use advanced machine learning techniques to build and refine predictive models to target specific groups or segments, run numerous what-if scenarios simultaneously, and process results for each group or segment without having to sort or index data each time.
Anti-financial crime optimization
Performs intelligent customer segmentation, entity resolution and scenario threshold tuning with above-the-line/below-the-line testing to generate more productive alerts, identify “true positives” and optimize overall transaction monitoring processes.
Cloud-native, elastic & scalable
Runs on SAS® Viya®, an elastic, scalable platform for public and private clouds. Rapidly processes large data sets and accelerates the complex analytics life cycle, from data preparation to discovery to deployment. The elasticity of compute and data environments supports growth in transaction volumes and complexity of model validation.
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