Using Segmented Models for Better Decisions

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Author: Mac Belniak

 

Abstract

 

Based on experience in developing thousands of segmented models, FICO has developed a segmentation search algorithm within the Segmented Scorecard module of FICO® Model Builder, and invoked by the SubPop Explorer module within FICO® Analytic Modeler Scorecard Professional, that enables modelers to combine pure machine learning with their own domain knowledge. With that, modelers can efficiently test innumerable combinations of segmentation variables, split points and split sequencing, and quickly derive the best possible segmentation schemes.   This paper describes the features of the Segmented Scorecard capability.

 

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