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.
|Number of pages||30|
|Journal||Annals of Operations Research|
|Early online date||23 Jan 2020|
|Publication status||Early online - 23 Jan 2020|
- Bank credit ratings