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This research investigates the contribution of women-owned businesses in driving economic development within the UAE, focusing on the primary elements influencing their success. A purposive sampling method was used to gather input from the Emirati businesswomen through a custom-designed questionnaire. Data were collected via various methods, including telephone interviews, email correspondence, and on-site visits where applicable. For analysis, the study employed partial least squares regression and structural equation modeling to assess both the measurement and structural frameworks. The evaluation centered on four key dimensions: individual attributes, organizational internal and external elements, support mechanisms, and the impact of national cultural norms. According to the results, business outcomes are positively influenced by individual traits, cultural context, external conditions, and support networks, whereas internal factors appear to lack significant influence. Notably, while the prevailing national culture enhances the overall performance of women-led ventures, it appears to impair the function of support systems. The research sheds light on the essential enablers and cultural limitations shaping the success of female entrepreneurs in the UAE.

This study aims to enhance credit risk identification, improve loan borrower review efficiency, and increase default prediction accuracy rate using data mining and machine learning techniques. The study also employs deep learning to develop a consumer loan default prediction model that minimizes credit risks and ensures consistent development. The researchers collected data from a survey of 1000 participants, stratified into local and foreign banks, and selected the top 11 banks based on turnover and customer volume. To construct the machine learning model, Keras, a neural network library that runs on TensorFlow, was utilized. The model predicts loan applicant default likelihood. The study's practical implications demonstrate a noteworthy success rate of customer default prediction, which can significantly benefit banks. The model was evaluated on a test set of 250 records and achieved a test set accuracy of 95.2%, correctly predicting the default state of 238 out of 250 respondents.

The paper examines four main sources of financial risk exposure for four banks in the United Arab Emirates during the years 2003 to 2009. It begins by measuring stability levels for different types of financial risks using the coefficient of variation measure. The research then proceeds to investigate the nature of the relationship between financial risk and the actual reported financial performance of each company, namely the return on equity and return on assets. The findings show that all four sources of financial risk showed significant stability while both profitability indicators exhibited significant instability over the same period. Moreover, performance on the return on assets indicator was strongly and positively tied to a company’s return on equity indicator across the four banks but exhibited little or no interconnection with the four types of risks that banks are commonly exposed.

The purpose of this study was to analyze the dividend performance of eight UAE based banks between the years 2001 and 2005. The analysis was undertaken by examining three sets of financial ratios that are routinely used to measure bank dividend performance. The main ratios that were employed put a particular focus on the banks’ ability to pay dividends in relation to market value of its share, earnings and ability to cover the payments. Descriptive statistical analysis was used to rank the performance, measuring the dispersion and the stability-variability of the indicators. Conclusions were then drawn from the computation of the descriptive analysis of ratios that allowed the author to make an effective comparison of said banks. This type of analysis was used to summarize the performance of each bank based on three criteria, mean, standard deviation and coefficient of variation of each banks performance. The findings showed that eight banks performed reasonably well during the period studied, but have different strategies in paying their dividends across the years under study. The analysis reveals that these banks have been affected by both internal and external factors.