In this webinar, participants will learn how AI improves the forecasting of financial documents, including balance sheets, income statements, and cash flow statements, enhancing predictive financial modeling for more accurate projections.
"Financial Modeling with Gen AI Capabilities" is a cutting-edge course designed to equip finance professionals with the skills to incorporate General AI (Gen AI) into financial modeling. Over a comprehensive 90-Minute session, the course delves into the transformative impact of Gen AI on financial analysis and decision-making processes.
The course begins by introducing the fundamentals of Gen AI in financial modeling. It addresses how Gen AI can be used to generate assumptions, leading to more accurate and reliable financial models. This is crucial in a world where financial forecasts and analyses must be both robust and adaptable.
One of the key focuses is on financial statements forecasting using Gen AI. Participants will learn how AI can enhance the forecasting of balance sheets, income statements, and cash flow statements. This section is particularly vital for understanding how AI can automate and refine the predictive aspects of financial modeling, allowing for more nuanced and comprehensive financial projections.
A significant portion of the course is dedicated to the practical application of Gen AI in creating financial models using Excel. This includes gathering and cleaning data, defining inputs and outputs, and structuring models effectively. The course demonstrates how Gen AI can streamline these processes, enhancing efficiency and accuracy.
The Integration of General AI (Gen AI) into financial modeling can evoke Fear, Uncertainty, and Doubt (FUD) for several reasons:
Each of these aspects contributes to a hesitancy among professionals to fully embrace Gen AI in financial modeling, necessitating education and transparent dialogue about the technology's capabilities and limitations.
Unlimited Viewing Recorded Version for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)