Credit rating ranking of Iranian banks based on CAMELS and hybrid multi-criteria decision analysis methods in uncertain environments
by Amir Karbassi Yazdi; Precious Okereke; Peter Fernandes Wanke; Seyed Arash Shahr Aeini; Amir Mehdiabadi
International Journal of Operational Research (IJOR), Vol. 49, No. 3, 2024

Abstract: This research aims to rank Iranian banks by CAMELS and multi-criteria decision analysis (MCDA) methods in uncertain environments. Ranking banks can lead to a better understanding of how customers select them and use their services. Since there is close competition between private and government banks in Iran, the most popular rating system (CAMELS) can help customers gain a better understanding of their situation. The CAMELS method consists of a rating based on bank performance factors. For finding the best bank in Iran once the CAMELS factors are considered, banks are then ranked by the COmbined COmpromise SOlution (CoCoSo) method, which also requires the stepwise weight assessment ratio analysis (SWARA) method to be used. The environment, however, is changing, thus affecting decision makers (DMs), so using uncertainty methods such as Pythagorean fuzzy numbers (PFN) is essential, which helps DMs make better decisions. The sample population of this research is eight public banks in Iran. The result indicates the best bank based on CAMELS and MCDA methods in uncertain environments with the result also pointing out how banks with a lower performance can do benchmarking to improve their performances according to CAMELS factors.

Online publication date: Mon, 04-Mar-2024

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