A STUDY ON THE ROLE OF ARTIFICIAL INTELLIGENCE IN FINANCIAL FORECASTING

The increasing complexity of financial markets and the exponential growth of data have necessitated the adoption of advanced analytical tools for accurate forecasting. Artificial Intelligence (AI) has emerged as a transformative technology in financial forecasting by enabling data-driven decision-making and predictive analytics. This study investigates the role of AI in enhancing the accuracy, efficiency, and reliability of financial forecasting models. The primary research problem addressed in this study is the limitation of traditional forecasting methods in handling large datasets and capturing non-linear market dynamics. The study aims to examine the relationship between AI techniques and forecasting accuracy and to analyze the impact of AI-driven models on financial decision-making.

A quantitative research design is adopted using secondary data collected from financial reports and AI-based forecasting applications. Statistical tools such as correlation and regression analysis are employed to test the hypotheses. The findings suggest that AI significantly improves forecasting accuracy and provides timely insights compared to conventional methods. The study contributes to the existing literature by offering empirical evidence on the effectiveness of AI in financial forecasting and highlights its implications for investors, financial analysts, and policymakers.