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Despite the turmoil in the global financial sector over the years, Asian banking stood still with many positive characteristics - stable, balanced competition, good governance, and profitable – becoming a fertile ground for performance studies. This paper departs from previous banking performance studies in Asia by proposing a novel stochastic Multi-Criteria Decision-Making (MCDM) based on sign decomposition, offering a novel perspective in five analytical fronts. First, criteria decorrelation and filtering from country and time impacts as an initial data treatment. Second, endogenous computation of bank criteria importance for the alternatives comprised by each bank and year under analysis, in a "one-stop-shop" approach. Third, derivation of partial performance scores for each criterion under each alternative, besides traditional overall performance scores for each alternative. Fourth, mapping the exogenous/endogenous relationships among bank filtered criteria from country and year impacts using transfer entropy. Fifth, prediction of the overall performance drivers in terms of country-related contextual variables using neural networks. Our findings indicate that bank liquidity, bank capitalization, net income as well as the ability to generate profit for the shareholders are significantly related to bank performance. In addition, we find that accounting standards have a significant impact on bank performance. Although inflation is found to be positively related to bank performance, the results show that bank performance is helpful to promote people's economic standard and life expectancy. Our study provides important implications to macroeconomic management to balance the development of macroeconomic development and bank performance. [ABSTRACT FROM AUTHOR]