Going beyond the mere gender diversity in the boardroom, this systematic review comprehensively covers the research on board diversity of financial institutions. More specifically, we cover gender diversity, as well as other characteristics of diversity, such as nationality, age, tenure, experience, education, ethnicity, and religion. A systematic literature review was employed using Scopus and Web of Science databases, covering all publications until May 2020, which resulted in 91 studies from 66 top‐ranked journals in accounting, finance, and economic fields. We analyze them based on the journal, methodology, research construct questions, and theoretical perspectives. Our results highlight the substantial knowledge gaps and the inconsistent findings of prior studies on several aspects of the field, suggesting avenues for further studies in terms of research designs, settings, scope, and theories. We argue that there is a need to explore other board diversity attributes rather than focusing on the gender diversity of the boards of financial institutions to achieve sustainable development. Also, more work is outlined on topics related to board diversity of financial firms that receive limited attention from scholars, such as (but not limited to) environmental performance, capital structure, intellectual capital, innovation and earnings quality of financial institutions, as well as the indirect effect of policy settings.

PurposeThis study aims to see the influence of a balanced scorecard (BSC) to determine the performance of banks in Palestine. Among the institutions that influence the economy of any country is the banking sector. Despite the influence of this sector on the economic policies and implementation in Palestine, there appears to be the difficulty of the appropriate approach to measuring its performance. Various techniques have failed to be efficient and effective. It creates an impulse to investigate the impact of a BSC in estimating the performance of banks in Palestine.Design/methodology/approachThis study adopted a descriptive design of the ex-post facto type with a sample of 126 senior bank staff randomly selected from fourteen Palestinian banks. In total, 3 hypotheses were raised and tested using Pearson's product-moment correlation analysis and multiple linear regression analysis at 0.05 level of significance.FindingsThe result showed that bank performance positively correlated with internal business process perspective (r = 0.633, p < 0.01), followed by customers’ perspective (r = 0.338, p < 0.01), financial perspective (r = 0.321, p < 0.01) and learning and growth perspective (r = 0.230, p < 0.01). While regression analysis showed that the most potent factor was internal business process perspective (Beta = 0.670, t = 10.320, p < 0.01), followed by learning and growth perspective (Beta = 0.185, t = 2.812, p < 0.01) and customers’ perspective (Beta = 0.150, t = 2.469, p < 0.05) and financial perspective (Beta = 0.100, t = 2.200, p < 0.05). This implies that a unit increase in internal business process perspective, learning and growth perspective and customer's perspective will increase bank performance by 67%, 18.5%, 15% and 10%, respectively.Practical implicationsAmong others, it was recommended that employees be exposed to the BSC model and its principles through continuous train as to ensure adequate application and implementation for enhanced bank performance. Administrators and stakeholders should ensure that the properties of each dimension of the BSC model are adequately worked on for easy fulfillment of the potentials in the model. It creates an avenue for a full-fledge organization with a workable customer, financial, internal business process, learning and growth perspective.Originality/valueThis is an initial study that used a BSC to determine the performance of banks in Palestine. Prior researchers overlook BSC dimensions composite and relative effect on the prediction of bank performance in Palestine.

No abstract

Data mining and machine learning (ML) methods are being used more than ever before in cyber security. The use of machine learning (ML) is one of the potential solutions that may be successful against zero day attacks, starting with the categorization of IP traffic and filtering harmful traffic for intrusion detection. In this field, certain published systematic reviews were taken into consideration. Contemporary systematic reviews may incorporate both older and more recent works in the topic of investigation. All of the papers we looked at were thus recent. Data from 2016 to 2021 were utilized in the study. Both security professionals and hackers use data mining capabilities. Applications for data mining may be used to analyze programme activity, surfing patterns, and other factors to identify potential cyber-attacks in the future. Utilizing statistical traffic features, ML, and data mining approaches, new study is being conducted. This research conducts a concentrated literature review on machine learning and its usage in cyber analytics for email filtering, traffic categorization, and intrusion detection. Each approach was identified and a summary provided based on the relevancy and quantity of citations. Some well-known datasets are also discussed since they are a crucial component of ML techniques. On when to utilize a certain algorithm is also offered some advice. On MODBUS data gathered from a gas pipeline, four ML algorithms have been evaluated. Using ML algorithms, different assaults have been categorized, and then the effectiveness of each approach has been evaluated. This study demonstrates the use of ML and data mining for threat research and detection, with a focus on malware detection with high accuracy and short detection times.

The research aimed to identify the extent of the commitment of Islamic banks in the city of Hebron to disclose social responsibility in the published financial statements, where a questionnaire was designed to answer the study questions. The questionnaires were distributed to all workers in Islamic banks operating in the city of Hebron, and the study concluded that the extent of The commitment of Islamic banks to disclose social responsibility in the financial data published in the city of Hebron was a high degree within its social responsibility, and the results also showed that there are obstacles when Islamic banks in the city of Hebron disclosed their activities in the areas of social responsibility, and the researchers have recommended the necessity of providing training courses for workers In Islamic banks, to introduce them to the strategy of disclosing social responsibility and its importance, as one of the strategies that contribute to achieving excellence in performance in general, and the need for the Monetary Authority to issue special legislation, related to the adoption of Islamic banks to disclose their commitment to social responsibilities due to its implications for the performance of society.