This study presents a data envelopment analysis (DEA) approach for ranking and optimisation of branches of a large bank based on financial indicators. The effective financial indicators are evaluated by standard organisational and managerial assessment. Then, robust DEA models are applied to rank and optimise the organisation using output-oriented models to evaluate management and technical efficiency. The models are output-oriented because they are the primary decision variables in banking institutions. Principal components analysis (PCA) and numerical taxonomy (NT) are used and applied to verify and validate DEA findings. The superiority and applicability of the algorithm are shown for various branches of a large private bank in Iran. In summary, the unique features of this study are: (1) utilisation of DEA models for ranking and optimisation of technical and management efficiency in a large private bank. (2) utilisation of a robust PCA–NT approach for verification and validation of DEA approach. The proposed framework can be used to study the behaviour of financial operations in large banks.