Book Details
Format
Paperback / Softback
Book Series
BestMasters
ISBN-10
3658401796
ISBN-13
9783658401795
Edition
1st ed. 2022
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint
Springer Gabler
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Dec 8th, 2022
Print length
83 Pages
Product Classification:
Financial services industry
Ksh 14,400.00
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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 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.
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