FICO® Model Translator

Translate, execute and quickly deploy SAS models

Overview

FICO® Model Translator

Companies are challenged with using their data effectively to deliver real time decisions with a customer focus. A key step to deploying analytics is to translate an analytic model into a decision system.

FICO® Model Translator rapidly converts SAS Programming Language into a decision service for deployment into a broad range of platforms including web services, Java, Spark and COBOL. This provides organizations with greater accuracy, speed of deployment, and reduced costs. 

View More on FICO® Blaze Advisor

View More on FICO® Model Translator Java

View More on FICO® Model Translator SRL

Core Benefits

Increase speed and accuracy

Reduce licensing and training

Greater transparency and control

Increase speed and accuracy

FICO® Model Translator rapidly translates SAS code to SRL and ingests SRL within FICO Blaze Advisor to invoke decision services, thus reducing deployment time and latency of corrective iterations.

Reduce licensing and training

FICO® Model Translator eliminates the need for a separate SAS production environment which reduces the requirement for costly cross-platform training and support.

Greater transparency and control

FICO® Model Translator puts the control and logic in the hands of business users while creating an audit trail necessary for compliance.

Solution Architecture

FICO® Decision Management Suite

The FICO Decision Management Suite, along with the FICO Analytic Cloud, provides a comprehensive environment that makes it quick and easy to glean insights from data, and develop analytic models and decision services that operationalize those insights.  It seamlessly integrates analytics, decisioning, optimization, data visualization and exploration, rapid application development and other FICO Decision Management Platform capabilities to provide a complete and agile decisioning solution.

Key Features

  • Reduce SAS licensing costs by around 70%.
  • Deploying new and revised models in minutes instead of weeks or months will greatly improve speed to market, which will lower opportunity costs of delayed models.
  • A shorter cycle time for model deployment provides the agility to deploy more models that help drive decisions and to enhance existing models on a regularly basis.
  • Reduce operational exposure of manual coding errors missed through testing and consistently deliver a 100% match with no discrepancies.
  • Complete transparency exposes the logic behind the models and an audit trail is recorded with each transaction and execution, helping meet compliance requirements.
  • Business analysts and stakeholders can have complete control over the life cycle of analytic models based on business objectives instead of IT release cycles.

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