Predicting SME’s default: Are their websites informative?

Predicting SME’s default: Are their websites informative?

We propose the use of online indicators, scraped from the firms’ websites, to predict default risk for a sample of Spanish firms via nonlinear discriminant analysis and the logistic regression model. •We propose online data as a new source of information for default prediction.•We compare online vs...

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Bibliographic Details
Published in:Economics letters Vol. 204; p. 109888
Main Authors: Crosato, Lisa, Domenech, Josep, Liberati, Caterina
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01-07-2021
Elsevier Science Ltd
Subjects:
Corporate websites
Default
Default risk
Discriminant analysis
Nonlinear discriminant
Regression analysis
SMEs
Web scraping
Websites
Web scraping
Corporate websites
Nonlinear discriminant
Default risk
SMEs
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Description
Summary:We propose the use of online indicators, scraped from the firms’ websites, to predict default risk for a sample of Spanish firms via nonlinear discriminant analysis and the logistic regression model. •We propose online data as a new source of information for default prediction.•We compare online vs offline data to predict default for a Spanish SMEs’ sample.•Online data scraped from the firms’ websites provide a better default prediction.•Kernel Discriminant refines default prediction with respect to Logistic Regression.
ISSN:0165-1765
1873-7374
DOI:10.1016/j.econlet.2021.109888