Modeling the efficiency of banks by cover data method and Genetic programming

Performance assessment of organizations in making strategic decisions for the future is essential. Thus, the efficiency determinations of organizations through planned economic growth in the future system loads are necessary. One of the most important indicators of performance evaluation is measuring efficiency. Banks are one of the most important economic units that provide proper conditions for growth and development in different sectors of a country's economy. Efficient banks can help economic growth, and poor performance may cause a crisis. The banking industry performs an important role in the process of Iran's economic development, and the structure of the financial system in Iran has turned from a controlled system into a liberalized one. In this paper for the first time in the Iranian banking industry, the performance trends and operation outcome of the banks are modelled by the Genetic Programming approach and the efficient performance is reported according to different employed parameters. This paper uses data envelopment analysis (DEA) to investigate the technical efficiency of the Iran banking industry over the period 2006-2012 by perspective methods of constant returns to scale and variable returns to scale. Consequent to technical efficiency evaluation, the scale efficiency is calculated. Results show a relatively good level of efficiency of the Iranian banking industry. In this article, we will try to study the performance of banks and compare it with each other and from the beginning of 2012 to the end of 2017 to provide an appropriate comparative analysis in this field. Finally, the technical efficiency was measured by yield relative to the constant scale and yield relative to the variable scale by the output nature of the axis.