Introduction to R for Quantitative Finance

Getting started with credit scoring in R

R provides powerful statistical tools for credit scoring. We emphasize here some of the most common techniques, namely probability default estimation with logit and probit regressions and ROC curve analysis. During both behavioral and application credit scoring, one can estimate or score the probability of default in the usual way that the theory of cross-sectional econometrics suggests.

Logit and probit regressions are generalized linear regression models with binary, dependent variables, where the two outcomes can be, for example, either defaulted or not. Logit regression uses logistic function; the probit model applies a cumulative distribution function of the standard normal distribution for estimating ...