國立虎尾科技大學 |

Application of AI in Credit Scoring Modeling

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Application of AI in Credit Scoring Modeling/ by Bohdan Popovych.
作者:	Popovych, Bohdan.
面頁冊數:	XV, 83 p. 22 illus. Textbook for German language market.online resource. :
Contained By:	Springer Nature eBook
標題:	Financial services industry. -
電子資源:	https://doi.org/10.1007/978-3-658-40180-1
ISBN:	9783658401801

Application of AI in Credit Scoring Modeling
Popovych, Bohdan.

Application of AI in Credit Scoring Modeling[electronic resource] /by Bohdan Popovych. - 1st ed. 2022. - XV, 83 p. 22 illus. Textbook for German language market.online resource. - BestMasters,2625-3615. - BestMasters,.

Introduction -- Theoretical Concepts of Credit Scoring -- Credit Scoring Methodologies -- Empirical Analysis -- Conclusion -- References.

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. About the author 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.

ISBN: 9783658401801

Standard No.: 10.1007/978-3-658-40180-1doiSubjects--Topical Terms:

570048
Financial services industry.

LC Class. No.: HG1501-3550

Dewey Class. No.: 332.17

Application of AI in Credit Scoring Modeling
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