Back to Search
Start Over
Can we trust machine learning to predict the credit risk of small businesses?
- Source :
- Review of Quantitative Finance & Accounting; Oct2024, Vol. 63 Issue 3, p925-954, 30p
- Publication Year :
- 2024
-
Abstract
- With the emergence of Fintech lending, small firms can benefit from new channels of financing. In this setting, the creditworthiness and the decision to extend credit are often based on standardized and advanced machine-learning techniques that employ limited information. This paper investigates the ability of machine learning to correctly predict credit risk ratings for small firms. By employing a unique proprietary dataset on invoice lending activities, this paper shows that machine learning techniques overperform traditional techniques, such as probit, when the set of information available to lenders is limited. This paper contributes to the understanding of the reliability of advanced credit scoring techniques in the lending process to small businesses, making it a special interesting case for the Fintech environment. [ABSTRACT FROM AUTHOR]
- Subjects :
- CREDIT ratings
LOANS
BORROWING capacity
SMALL business
MACHINE learning
CREDIT risk
Subjects
Details
- Language :
- English
- ISSN :
- 0924865X
- Volume :
- 63
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Review of Quantitative Finance & Accounting
- Publication Type :
- Academic Journal
- Accession number :
- 179872591
- Full Text :
- https://doi.org/10.1007/s11156-024-01278-0