A dimension reduction assisted credit scoring method for big data with categorical features

In the past decade, financial institutions have invested significant efforts in the development of accurate analytical credit scoring models. The evidence suggests that even small improvements in the accuracy of existing credit-scoring models may optimize profits while effectively managing risk expo...

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Veröffentlicht in:	Financial innovation (Heidelberg) Jg. 11; H. 1; S. 29 - 30
Hauptverfasser:	Miljkovic, Tatjana, Wang, Pei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Heidelberg Springer Nature B.V 01.12.2025 SpringerOpen
Schlagworte:	Accuracy Big Data Credit scoring Dimension reduction Financial institutions Logistic regression Majorization-minimization algorithm Methods
ISSN:	2199-4730, 2199-4730
Online-Zugang:	Volltext
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