ABSTRACT
This chapter proposes an integrated hybrid multiple criteria decision making (MCDM) model for predicting the financial performance of commercial banks. It aims to contribute the application of soft computing and MCDM methods in the banking industry. The chapter demonstrates that the three-stage model and examines a group of commercial banks as an empirical case. The first stage focuses on exploring and retrieving patterns—decision rules and indispensable attributes—from the historical data. The second stage adopts the core attributes from the first stage, induced from historical data, to form a decision-making trial and evaluation laboratory-based analytic network process decision model, which may indicate the directional influences among the attributes and the relative importance of each criterion. And the final stage modified vikor method is used to synthesize the performance gap of each bank for ranking or selection. The chapter provides an empirical case showing how to transform the analytics from the hybrid model into improvement planning.
