2023
DOI: 10.1111/exsy.13485
|View full text |Cite
|
Sign up to set email alerts
|

Evolutions in machine learning technology for financial distress prediction: A comprehensive review and comparative analysis

Kaoutar El Madou,
Said Marso,
Moad El Kharrim
et al.

Abstract: In recent years, financial distress prediction (FDP), also known as corporate failure prediction or bankruptcy prediction, has gained significant importance due to its impact on organizations, especially during unexpected events like pandemics and wars. Machine learning (ML) models have emerged as innovative and essential tools in predicting financial distress, leveraging the ever‐increasing volume of databases and computing power. This study utilizes bibliographic techniques to contribute to the field's liter… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
3
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
references
References 115 publications
0
0
0
Order By: Relevance