Credit rating prediction using a fuzzy MCDM approach with criteria interactions and TOPSIS sorting
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F25%3A39923433" target="_blank" >RIV/00216275:25410/25:39923433 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s10479-024-06183-2" target="_blank" >https://link.springer.com/article/10.1007/s10479-024-06183-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10479-024-06183-2" target="_blank" >10.1007/s10479-024-06183-2</a>
Alternative languages
Result language
angličtina
Original language name
Credit rating prediction using a fuzzy MCDM approach with criteria interactions and TOPSIS sorting
Original language description
Multi-criteria decision making (MCDM) provides effective methods for dealing with the challenge of sorting credit ratings. This paper presents a novel data-driven MCDM sorting approach to predicting credit ratings. Our methodology combines the fuzzy TOPSIS-Sort-C model with the fuzzy best-worst approach, supported by a fuzzy cognitive map, to effectively deal with criteria interactions. This approach provides a corporate credit risk assessment, taking into account the uncertainties in credit risk assessment and relevance of its criteria by using fuzzy c-means and correlation-based feature selection. Our empirical analysis of 1138 US companies demonstrates the reliability of our model in dealing with a range of financial and non-financial indicators. The results demonstrate the potential of our methodology in credit rating assessment, with a good predictive performance relative to existing models.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50204 - Business and management
Result continuities
Project
<a href="/en/project/GA22-22586S" target="_blank" >GA22-22586S: Aspect-based sentiment analysis of financial texts for predicting corporate financial performance</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Annals of Operations Research
ISSN
0254-5330
e-ISSN
1572-9338
Volume of the periodical
353
Issue of the periodical within the volume
Neuveden
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
29
Pages from-to
251-279
UT code for WoS article
001283259500003
EID of the result in the Scopus database
2-s2.0-85200343980