Author(s): Ahmad Ali, Minhas Akbar, Ing. Libuse Svobodova
Islamic banking has witnessed a phenomenal growth worldwide and has been at the forefront of academic discussion in recent years. The present research employs financial ratios to compare the performance indicators of liquidity, profitability, insolvency risk and asset composition in Islamic and conventional banks of Pakistan. We use diverse econometric approaches such as univariate analysis and logistic regression to analyze the financial ratios of Islamic and conventional banks. While neural network analysis is applied to uncover the most important ratios in the banking industry. The findings reveal that, on average profitability for conventional banks is higher than Islamic banks. In contrast, credit and insolvency risk is higher for Islamic banks than their conventional counterparts. Results of neural network analysis entail that deposit to assets ratio and return on equity are most important financial indicators in the banking industry. While, loans to deposits ratio is the least important indicator. Study has useful implications especially for Islamic banking industry. The policy makers of these banks should strive to optimize profitability and introduce new tools to curtail the credit and insolvency risk. Profitability can be increase by focusing on increasing turnover, efficiency, productivity, and decreasing costs. It can be overcome by thoroughly checking clients’ past credit history, limiting the credit level, insurance the credit risk, etc.