Author: Kuziev, Asadbek Shakir ugli

Annotation: Artificial intelligence (AI) has emerged as a transformative force in the financial sector, fundamentally altering how organizations analyze data, assess risk, and make strategic decisions. Financial institutions increasingly deploy machine learning, deep learning, natural language processing, and generative AI to improve forecasting accuracy, optimize portfolios, detect fraud, and automate credit assessments. This article examines the role of AI in financial decision-making through a review of recent scholarly literature and a qualitative synthesis of current applications. The study finds that AI significantly enhances decision quality by processing large and complex datasets, identifying nonlinear patterns, and generating timely insights that often outperform traditional statistical models. AI also improves operational efficiency and supports more objective and consistent decision processes. However, several challenges remain, including model opacity, algorithmic bias, cybersecurity vulnerabilities, regulatory uncertainty, and concerns related to financial stability. The findings suggest that AI is most effective when used as a decision-support tool rather than a complete substitute for human judgment. The article concludes that organizations should adopt explainable and ethically governed AI systems while maintaining robust oversight and regulatory compliance.

Keywords: Artificial Intelligence; Financial Decision-Making; Machine Learning; Risk Management; Algorithmic Trading; Financial Technology

Pages in journal: 764 - 768