IEEE Access, v. 10, pp. 54098 – 54109. Abstract: This paper provides a new perspective on the performance of ASEAN member countries’ banks as proxied by CAMELS rating system in the light of information reliability. A comprehensive MCDM approach is developed based on alternative methods to handle expert preference uncertainties regarding banking ideal performance levels and relative CAMELS variable efficiency. While expert preferences are collected using structured interviews, the partial bank rankings are defined upon Fuzzy TOPSIS with the primary relative efficiency weights obtained from SWARA. Z-numbers are utilized to address the inherent fuzziness in how banking performance and financial distress are associated with information reliability of positive-ideal banking performance and CAMELS variables efficiency functions generated from expert preferences or perceptions. The empirical findings demonstrated that employing information reliability methodologies applied to a proxy of the CAMELS rating system, the ambiguous influence of ASEAN banking performance on financial hardship can be adequately handled.
Keywords: Banking, Economics, Reliability, Computational modeling, Biological system modeling, Business, Power system reliability.