Business & Economics Books:

Application of AI in Credit Scoring Modeling

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Description

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 Biography:

MA Bohdan Popovych is a data scientist and a researcher in quantitative finance. The main scientific focus of the author is application of advanced analytics and artificial intelligence in finance and economics.
Release date Australia
December 8th, 2022
Audience
  • Professional & Vocational
Edition
1st ed. 2022
Illustrations
22 Illustrations, black and white; XV, 83 p. 22 illus. Textbook for German language market.
Pages
83
ISBN-13
9783658401795
Product ID
36123864

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