A multicriteria decision support tool for modelling bank credit ratings

We introduce an application of the SMAA-Fuzzy-FlowSort approach to the case of modelling bank credit ratings. Its stochastic nature allows for imprecisions and uncertainty that naturally surround a decision-making exercise to be embedded into the proposed framework, whilst its output complements the...

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Bibliographic Details
Published in:Annals of operations research Vol. 306; no. 1-2; pp. 27 - 56
Main Authors: Gaganis, Chrysovalantis, Papadimitri, Panagiota, Tasiou, Menelaos
Format: Journal Article
Language:English
Published: New York Springer US 01.11.2021
Springer
Springer Nature B.V
Subjects:
Analysis
Banking industry
Business and Management
Combinatorics
Credit ratings
Decision analysis
Decision making
Decision support systems
Financial institutions
Greece
Industrial research
Management science
Methods
Modelling
Multiple criterion
Operations research
Operations Research/Decision Theory
Ratings
Regression analysis
Risk (Economics)
S.I.: Regression Methods based on OR techniques
Theory of Computation
United Kingdom
Greece
United Kingdom
C53
GAIA
MCDA
G21
G24
C38
Bank credit ratings
SMAA
FlowSort
ISSN:0254-5330, 1572-9338
Online Access:Get full text
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Summary:We introduce an application of the SMAA-Fuzzy-FlowSort approach to the case of modelling bank credit ratings. Its stochastic nature allows for imprecisions and uncertainty that naturally surround a decision-making exercise to be embedded into the proposed framework, whilst its output complements the ordinal nature of a crisp classification with cardinal information that shows the degree of membership to each rating category. Combined with the SMAA variant of GAIA that offers a visual of a bank’s judgmental analysis, both recent approaches provide a holistic multicriteria decision support tool in the hands of a credit analyst and enable a rich inferential procedure to be conducted. To illustrate the assets of this framework, we provide a case study evaluating the credit risk of 55 EU banks according to their financial fundamentals.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-020-03516-9