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Application of AI in Credit Scoring Modeling (BestMasters)

By: Bohdan Popovych (Author)

Extended Catalogue

Ksh 18,250.00

Format: Paperback or Softback

ISBN-10: 3658401796

ISBN-13: 9783658401795

Collection / Series: BestMasters

Collection Type: Publisher collection

Edition statement: 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

Publication Status: Active

Product extent: 83 Pages

Product Classification / Subject(s): Financial services industry

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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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