THE ROLE OF ARTIFICIAL INTELLIGENCE IN FINANCIAL ANALYSIS: INTEGRATION AND NECESSITY

Abstract

The increasing availability of large and complex financial datasets has intensified the need for advanced analytical tools, positioning artificial intelligence (AI) as a critical component of contemporary financial analysis. This paper investigates the role of artificial intelligence in financial analysis, with a particular focus on its integration into traditional analytical frameworks and its growing necessity in modern financial decision-making. The study is based on a qualitative methodological approach, combining a systematic review of relevant academic literature with an analytical examination of current AI applications in financial forecasting, risk assessment, and anomaly detection. The research results indicate that while artificial intelligence-based techniques—primarily machine learning algorithms and natural language processing—possess the potential to enhance efficiency, they exhibit significant vulnerability regarding accuracy when processing unstructured tables, leading to exponential error propagation and the systemic convergence of inaccurate results within complex financial indicators. The paper argues that artificial intelligence does not replace human expertise, but rather enhances and accelerates the analytical role of financial professionals by supporting more informed, evidence-based decision-making.