Using Principal Component Analysis in Loan Granting.

This paper describes the utility of Principal Component Analysis (PCA) in the banking domain, more exactly in the consumer lending problem. PCA is a powerful tool for analyzing data of high dimension. When an applicant requests a loan for personal needs, a credit officer collects data from him and makes a scoring. The factors analyzed can be significant as well as insignificant. The principal component analysis can help in this case to extract those factors, which produce a better credit scoring model. The data set used for the analysis is provided by a public database containing credit data from a German bank. The results emphasize the utility of PCA in the banking sector to reduce the dimension of data, without much loss of information. [ABSTRACT FROM AUTHOR]