SAS^® Adaptive Learning and Intelligent Agent System

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.

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.

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.

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.

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