Benchmarking of bank performance using the life cycle concept and the DEA approach

Abstract

Despite the widespread use of benchmarking as an effective tool for improving the efficiency of the bank’s functioning, its implementation does not take into account the relation between comparable performance indicators, the choice of benchmark for comparison, deviations of indicators from target values with stages of the bank’s life cycle, which cause differences in the intensity and characteristics of development of fnancial institutions. The procedure for identifying a reference bank for comparison is also insufficiently specified, which is important in terms of adapting its experience by the recipient bank due to the possible fundamental differences in their functioning. Therefore, the article has modified the technology of benchmarking of the bank’s performance based on the life cycle concept and the DEA approach. Te research is based on the use of the DEA method to determine the most efcient bank as a reference bank in benchmarking comparison; canonical analysis – for the formation of a list of indicators of bank performance; cluster analysis – to substantiate the levels of deviations of the actual values of comparable indicators from the target ones. Te study envisages, firstly, the selection of indicators for benchmarking comparisons based on the identification of causal relationships between the indicators of subsystems “Finance”, “Customers”, “Business processes”, “Personnel development” that arise at each stage of a bank’s life cycle; secondly, the choice of a benchmark bank for comparison according to the maximum value of the performance indicator calculated through the DEA method for a set of banks that are at one and the same stage of their life cycle; thirdly, definition of the range of deviations (low, permissible, critical) of the actual values of comparable indicators of the effectiveness of management of finance, customer base, business processes and personnel of the bank from the target ones. A practical testing of the benchmarking technology was carried out on the example of Ukrainian banks, whose stage in 2016 was identified as “intense growth”.