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Overview: How to assess the credit risk has become crucial for credit card companies and commercial banks due to the explosive growth of credit market in recent years. Logistic Regression, which is a special case of Generalized Linear Models, is the most widely used statistical model in the credit scoring industry. Introduced by McCullagh and Nelder, Generalized Linear Models provide a unified framework to model response from any member of the exponential family distributions, such as Gaussian, Binomial, or Poisson. This paper presented in SAS Global Forum introduces Generalize Additive Model as a promising alternative to Logistic Regression for credit scoring.
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