Integration Between Artificial Intelligence and Financial Budgets to Achieve Financial Control in Insurance Companies: An Applied Study at Al-Rasheed Bank

Abstract

The aim of this study was to demonstrate the impact of the integration between artificial intelligence and financial budgets in maintaining financial controls for insurance companies, using the method of the applied study with Al-Rasheed bank as a case study. The study was done on the basis of descriptive-analytical methodology using the opinions of some employees in the fields of finance, budgeting, auditing, controlling, and information technology at the bank as well as using some data related to finance and budget reports. The study examined the reality of the budgets in the traditional financial system in comparison with the budgets based on the support provided by AI methods, including those based on predictive analytics and machine learning tools for estimating revenues and expenses, as well as detecting financial deviations. The findings included a considerable decline in the rates of financial deviations under the budgets with AI support when they moved from high levels under the traditional budgets to low levels. At the same time, the results revealed an improvement in financial performance indicators, particularly in terms of report preparation speed, estimation accuracy, and improvement in the preventive control process as well as concurrent control, which is significant to financial decision-making. The study concluded that the integration of AI in the process of preparing financial budgets in insurance companies and banks is an effective tool to improve financial control, reduce financial risks, and enhance financial performance efficiency in those institutions.