Machine learning for credit risk in the Reactive Peru Program: A comparison of the Lasso and Ridge Regression models

COVID-19 has caused an economic crisis in the business world, leaving limitations in the continuity of the payment chain, with companies resorting to credit access. This study aimed to determine the optimal machine learning predictive model for the credit risk of companies under the Reactiva Peru Pr...

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Veröffentlicht in:	Economies Jg. 10; H. 8; S. 1 - 21
Hauptverfasser:	Geraldo-Campos, Luis Alberto, Soria, Juan J, Pando-Ezcurra, Tamara
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI 01.07.2022 MDPI AG
Schlagworte:	Banks Beneficiaries Comparative analysis Coronaviruses COVID-19 Credit risk credits Economic aspects Economic crisis Epidemics Financial risk Lasso model Loans Machine learning Measuring instruments Pandemics Peru Quality control Regression analysis Ridge model Stockholders Swaps (Finance) Working capital Peru
ISSN:	2227-7099, 2227-7099
Online-Zugang:	Volltext
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