The Role of Big Data and Artificial Intelligence in Analytical Analysis of Financial Indicators
Ilaha Asadullayeva
Abstract. In the modern economic environment, the rapid growth in the volume of financial data and its diversification across multiple sources have made analytical processes more complex. Traditional financial analysis methods have limited capabilities in processing large-scale and heterogeneous datasets, which has led to the need for advanced technological approaches. In this context, Big Data and Artificial Intelligence (AI) technologies play a significant role in the analytical evaluation of financial indicators. Big Data technologies enable the collection, storage, and processing of large datasets obtained from various sources, including financial transactions, market indicators, and customer behavior. Artificial Intelligence, in turn, facilitates the development of analytical models, the identification of hidden patterns, and the generation of more accurate forecasts based on these datasets. In particular, machine learning techniques are widely applied in financial risk assessment and decision-making processes. This study examines the role of Big Data and AI in the analysis of financial indicators and evaluates their application potential. The results indicate that the use of these technologies enhances analytical accuracy, improves risk management, and increases the efficiency of decision-making processes. Consequently, they provide a significant competitive advantage in the modern financial system.
Keywords: Big Data, artificial intelligence, financial indicators, financial analysis, risk management, forecasting, machine learning, deep learning, financial technologies (FinTech), analytical models