Dynamic Cash Flow Management Under Uncertainty: Integrating Scenario Planning and Advanced Analytical Tools

Effective cash flow management is essential for ensuring financial stability and operational success in dynamic and uncertain environments. Traditional methods often fall short in addressing the complexities posed by volatile markets and unforeseen economic shifts. This paper explores the integration of advanced AI-based analytical tools, scenario planning, and predictive modeling to enhance cash flow optimization. By focusing on iterative processes of analysis, forecasting, and decision-making, the study provides a comprehensive framework for leveraging innovative technologies such as real-time monitoring systems, machine learning algorithms, and probabilistic simulations. Through the case study of the Kian Petrochemical project, the research highlights the transformative impact of these tools in achieving proactive financial management and mitigating risks. This paper contributes to bridging theoretical principles with practical applications, paving the way for more resilient financial systems capable of navigating modern economic uncertainties.

کلیدواژه ها:

Cash Flow Management ، Artificial Intelligence ، Scenario Planning ، Predictive Analytics