Credit-Scoring-Rule
Statistical Models to develop credit scoring rule for new applicants | R
Dataset
The German Credit dataset has data on 1000 past credit applicants, described by 30 variables. Each applicant is also rated as “Good” or “Bad” credit (encoded as 1 and 0 respectively in the Response variable). The GermanCredit.xls file contains the variable descriptions and the data. New applicants for credit can be evaluated on these 30 variables.
Problem Statement
We would like to develop a credit scoring rule that can be used to help determine whether a new applicant presents a good or bad credit risk.
Analysis and Statistical Models:
- Exploratory data analysis
- Decision Trees (CART)
- Random Forest
- Logistic Regression