AI-Based Financial Forecasting And Risk Analysis

Artificial Intelligence (AI) has significantly transformed financial forecasting and risk analysis by enabling more accurate, data-driven, and real-time decision-making processes. Traditional financial models often struggle to handle the complexity, volume, and volatility of modern financial data. AI-based techniques, including machine learning, deep learning, and predictive analytics, offer advanced capabilities for analyzing historical data, identifying patterns, and forecasting future market trends. This study explores the application of AI in financial forecasting and risk assessment, focusing on its ability to improve accuracy, efficiency, and adaptability in dynamic financial environments. It examines key AI models used in stock price prediction, credit risk evaluation, fraud detection, and portfolio optimization. The study also highlights the integration of AI with big data analytics and cloud computing to enhance scalability and real-time processing. Furthermore, it discusses major challenges such as data quality issues, model interpretability, regulatory compliance, and market uncertainty. Emerging trends such as explainable AI, reinforcement learning, and automated trading systems are also analyzed. The findings indicate that AI-based financial forecasting and risk analysis significantly improve decision-making and risk management in modern financial systems