A STOCHASTIC SETTING TO BANK FINANCIAL PERFORMANCE FOR REFINING EFFICIENCY ESTIMATES

This study contributes to develop a framework to measure the financial performance of banks in a stochastic setting. The framework comprises several steps, the first of which is the development of a financial performance measurement model to evaluate a bank's financial performance using a set of factors from the CAMEL (Capital adequacy, Assets, Management Capability, Earning and Liquidity) system. Second, the stochastic setting of the efficiency measurement is handled using the data collection budget allocation approach, whereby Monte Carlo simulations are used to analyse additional generated data and a genetic algorithm is used to refine the accuracy of the efficiency estimates. The results show that the accuracy of the model is greatly improved using the proposed approach. In contrast to the conventional deterministic model, the proposed framework is more useful to managers in determining the bank's future financial operations to improve the overall financial soundness of the bank. Copyright © 2014 John Wiley & Sons, Ltd.