Purpose Using capital asset pricing model (CAPM) and the Z-risk index based on weekly data, this study aims to estimate yearly unsystematic, total, three systematic and insolvency risks in the Gulf Cooperation Council (GCC) countries for the period 2010–2018. The findings of CAPM show positive systematic market risk exposure in all GCC countries for all years, which support the contribution of stock markets to bank prices and returns. The mixed signs of systematic interest rate and exchange rate risks in GCC countries provide hedging opportunities, diversification strategies and regional cooperation, which help risk managers to hedge and stabilize their portfolios against interest rate and exchange rate fluctuations. Therefore, it is necessary that managers and policymakers develop a monitoring system on factors affecting bank insolvency risks to avoid bankruptcies and insolvencies. Design/methodology/approach This study uses the three-factor CAPM and Z-risk index to measure six types of risks. The CAPM uses market information to estimate the sensitivity of banks to the fluctuations of equity markets, debt markets and foreign exchange markets. Sharpe (1964), Lintner (1965) and Treynor (1965) developed a single-factor CAPM and the coefficient of the model was called systematic market risk. The single-factor CAPM highlights stock markets as the only non-diversifiable source of systematic risks, whereas Stone (1974) and Jorion (1990) highlighted interest rate and exchange rate fluctuations as the other types of non-diversifiable systematic risks. The following functional form in equation (1) estimates five types of risks using CAPM. Findings The findings of CAPM show positive systematic market risk exposure in all GCC countries for all years, which support the contribution of stock markets to bank prices and returns based on CAPM theory. The mixed signs of systematic interest rate and exchange rate risks in GCC countries support hedging opportunities and diversification strategies which may help risk managers to hedge and stabilize their portfolios against the fluctuations of interest rate and exchange rate. Although, this policy may decrease the profits of banking sectors but at the same time it would stabilize the portfolios and prevent bankruptcies and big losses because of the fluctuations of interest rate. Moreover, a bank has a better chance to have more liquidity position during financial crises because of the diversifications into different regional markets. Research limitations/implications Therefore, this study contributes to the existing literature by using risk measurement by a three-factor CAPM and the Z-risk index as discussed further in methodology. Originality/value It is necessary that managers and policymakers develop a monitoring system on factors affecting bank insolvency risks to avoid bankruptcies and insolvencies.

This study aims to examine the impact of artificial intelligence on the effective applying of cyber governance in Jordanian commercial banks. The objectives are divided into identifying the impact of expert systems on cyber governance in Jordanian commercial banks, identifying the impact of neural networks on cyber governance in Jordanian commercial banks, identifying the impact of genetic algorithms on cyber governance in Jordanian commercial banks, and identifying the impact of smart agents on governance cyber ​​in Jordanian commercial banks, The current study population includes (13) Jordanian commercial banks listed on the Amman Stock Exchange and the study sample includes all employees in the accounting departments, internal auditors, and programmers. The researchers distributed (208) questionnaires to the study sample members electronically, at a rate of (16) questionnaires in each bank and retrieved them in the same way. Then, 208 questionnaires were retrieved, including (7) questionnaires that are not valid for analysis, due to following the pattern method in answering all paragraphs, so that the researcher has (201) questionnaires valid for statistical analysis, This indicates the interdependence between artificial intelligence techniques and applications (expert systems, neural networks, genetic algorithms, and smart agents) on the effective application of cyber governance in Jordanian commercial banks, as these technologies and applications contribute to enhancing the effectiveness of cyber governance. Thus, it is necessary for commercial banks in Jordan to rely more on advanced systems, so that banks can use modern computer equipment and software, and thus increase the dependence of these banks on the effective application of cyber governance to follow up the progress of business and tasks in accordance with its strategies.