SAS® Adaptive Learning and Intelligent Agent System Features

Anomaly detection

  • Combines supervised and unsupervised machine learning algorithms to detect fraud and other rare events.
  • Supports exporting/publishing of models to SAS Model Manager where other SAS tools can access the model.
  • Includes APIs that give you the flexibility to use other systems for record scoring, alert generation, classification and model retraining.
  • Presents charted anomaly detection results to help set alert thresholds and control volume of alerts generated.
  • Highlights top variables contributing to the anomalies through charts in the data set.
  • Provides an unsupervised scorecard to help interpret why a row was identified as anomalous.
  • Alerts on a percentage of records from below the threshold (below the line), reducing the potential for introducing bias into the model over time.
  • Enhances job monitoring – including improvements to job status, error handling and logging – which increases the accuracy of job progress status reporting.
  • Improves efficiency by duplicating models based on other model versions, reducing time to adjust variations of models for best results.

Transparency

  • Includes a white box model and record scorecard to take the mystery out of machine learning.
  • Delivers narrative, text and visuals for describing and interpreting models.
  • Allows analysts and investigators to provide transparency into decisioning and explain why someone was identified as fraudulent.

Adaptive learning

  • Creates an adaptive learning system that continually improves its ability to detect fraud and react rapidly to the emergence of new fraud patterns via integration with SAS Visual Investigator.
  • Feeds triage results (e.g., alert productivity ratings) from SAS Visual Investigator back into the training data for training new models.
  • Supports the entire analytics life cycle – from data, to discovery, to deployment.

Easy-to-use visual interface

  • Creates models for detecting rare events by selecting:
    • Training data tables that include records classified for fraud.
    • Target column containing fraud classifications.
    • Values that indicate fraud. 
    • Model complexity.
    • Variables to exclude or include.
  • Evaluates model effectiveness and selects appropriate alerting threshold.
    • Provides charts describing model accuracy. Compares values in the target column to the model’s classification of each record and charts the balance of false positives and negatives for each threshold.
    • Automates best threshold selection.
    • Lets you override the threshold with a threshold of your own.
    • Enables you to select a threshold and see the impact on false positives and negatives.
    • Supports multiple versions of a model for evaluation prior to deployment.
  • Deploy models at the click of a button, automatically creates a set of jobs for generating scores and alerts.

Automated integration

  • Automatically integrates with SAS Visual Investigator for scoring, alerting, triaging, refreshing training data and retraining models.

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