DEA in Banking
Data envelopment analysis (DEA) is a linear-programming-based method for assessing the performance of homogeneous organizational units and is increasingly being used in banking. The unit of assessment is normally the bank branch. Studies are mostly centered on deriving a summary measure of the efficiency of each unit, on estimating targets of performance for the unit, and on identifying role-model units of good operating practice. Additional uses for DEA in banking include the measurement of efficiency in light of resource and output prices, the estimation of operating budgets that are conducive to efficiency, the assessment of financial risk at bank-branch level, and the measurement of the impact of managerial change initiatives on productivity.
DEA tackles problems which might also be tackled using regression. DEA offers the advantage that it identifies an efficient rather than an average level of output against which the performance of individual units is judged. Further, while in regression we must specify in advance the functional form linking inputs to output, that is not necessary in DEA. This makes it possible to consider multiple inputs against multiple outputs in DEA while in regression we must either have a single input with multiple outputs or a single output with multiple inputs. Set against this there is a greater risk of distortion of results by outliers. It is normal to do several runs with different sets of inputs and outputs and check that the results are robust.
These two views are complementary and can be integrated into an overall assessment, as shown in Figure
