Application of AI in Credit Scoring Modeling (Paperback) (ISBN-13: 9783658401795)

The scope of this study is to investigate the capability of AI methods to accurately detect and predict credit risks based on retail borrowers' features. The comparison of logistic regression, decision tree, and random forest showed that machine learning methods are able to predict credit defaults of individuals more accurately than the logit model. Furthermore, it was demonstrated how random forest and decision tree models were more sensitive in detecting default borrowers.

Author: Bohdan Popovych
ISBN-10: 3658401796
ISBN-13: 9783658401795
Publisher: Springer Gabler
Language: English
Published: 12/08/2022
Pages: 83
Format: Paperback
Weight: 0.31lbs
Size: 8.27h x 5.83w x 0.24d