Application of AI in Credit Scoring Modeling
ISBN:
978-3-658-40179-5
Auflage:
1st ed. 2022
Verlag:
Springer Fachmedien Wiesbaden GmbH, Springer Gabler
Land des Verlags:
Deutschland
Erscheinungsdatum:
08.12.2022
Reihe:
BestMasters
Format:
Softcover
Seitenanzahl:
83
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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 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.
Schlagwörter
Biografische Anmerkung
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.
Social & Economic Studies within the Framework of Emerging Global Developments - Volume 5
Erscheinungsjahr:
2024
