مجلة الباحث الإقتصادي
Volume 13, Numéro 2, Pages 181-199
2025-12-30
Integrating Ai-driven Financial Modeling And Business Analytics For Optimized Forecasting And Investment Strategies
Authors : Azzouza Amani . Ghedabna Lilia .
Abstract
AI has revolutionized financial modelling and business analytics through improving precision and efficiency in investments. Models of finance tend to use historical approaches and statistical approaches, which are not effective in capturing complicated market trends and economic parameters. AI tools such as ML and DL, real-time data processing, risk management and portfolio optimization are a reality. This research seeks to identify in which ways AI improve the accuracy of financial forecasting and devise fresh strategies in investment through hydro-neural networks and algorithmic trading. This research uses both qualitative and quantitative data. For qualitative data, patterns and analyses of historical financial data from stock markets, economic indicators and corporate reports collected. The study tries to measure the capability of AI decision support systems by benchmarking them against conventional methods through back testing and validation metrics. It has discovered that the use of AI in financial modelling has drastically improved the quality of forecasting, risk assessment, and investment decisions. Businesses develop more advanced and mechanistically flexible strategies by merging machine learning with business analytics. The study highlights an important shift in the role of AI in finance and encourages its greater use in investment management and finance.
Keywords
Artificial Intelligence; Financial Modeling; Business Analytics; Machine Learning; Investment Strategies; Predictive Analytics; Forecasting Optimization.
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