Using Ordinal Regression to Build a Credit Scoring Model

A creditor wants to be able to determine whether an applicant is a good credit risk, given various financial and personal characteristics. From their customer database, the creditor (dependent) variable is account status, with five ordinal levels: no debt history, no current debt, debt payments current, debt payments past due, and critical account. Potential predictors consist of various financial and personal characteristics of applicants, including age, number of credits at the bank, housing type, checking account status, and so on.

This information is collected in german_credit.sav. See the topic Sample Files for more information. Use Ordinal Regression to build a model for scoring applicants.

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