About this paper
This paper illlustrates how Credit Scoring for SAS Enterprise Miner software is used to build credit scoring models for the retail credit industry. It discusses the benefits of performing credit scoring and the advantages of building credit scoring models in-house using SAS Enterprise Miner. It goes on to discuss the advantages and disadvantages of three important model types: the scorecard, the decision tree and the neural network. Finally, it presents a case study where an application scoring model is built with SAS Enterprise Miner, beginning with reading the development sample, through classing and selecting characteristics, fitting a regression model, calculating score points, assessing scorecard quality (in comparison to a decision tree model built on the same sample) and going through a reject inference process to arrive at a model for scoring the new customer applicant population.
SAS is the leader in analytics. Through innovative analytics, business intelligence and data management software and services, SAS helps customers at more than 80,000 sites make better decisions faster. Since 1976, SAS has been giving customers around the world THE POWER TO KNOW®.