Financial Modeling With Generative Ai
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.52 GB | Duration: 3h 28m
Published 11/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.52 GB | Duration: 3h 28m
Generative AI in Finance | GenAI Financial Modeling | Financial Risk Assessment GenAI | GenAI Predictive Modelling
What you'll learn
Evaluate the effectiveness of generative AI models for financial forecasting and risk assessment.
Construct financial models incorporating generative AI to enhance predictive capabilities.
Critique the use of GenAI for mitigating financial risk, emphasizing ethical considerations.
Design advanced scenario-based financial models using generative AI for strategic decision-making.
Requirements
A basic knowledge of financial modeling, forecasting, or risk assessment, proficiency in Excel, and interest in adopting AI tools for enhanced financial insights.
Description
Unlock the future of financial modeling with Generative AI! As financial landscapes evolve, generative AI is transforming the art and science of financial modeling, making predictions and scenario analysis more efficient and insightful.In this 3–4-hour course, you will explore how GenAI tools revolutionize financial modeling, enabling you to make data-driven predictions, automate workflows, and enhance decision-making with AI-powered insights.Learn to automate cash flow forecasting, create predictive models for investment analysis, and build AI-driven risk assessments—all through hands-on examples, demonstrations, and real-life case studies.By the end, you'll be equipped to leverage GenAI for smarter financial decisions, enhanced efficiency, and staying ahead in the dynamic finance industry.Learning Objectives:Evaluate the effectiveness of generative AI models for financial forecasting and risk assessment.Construct financial models incorporating generative AI to enhance predictive capabilities.Critique the use of GenAI for mitigating financial risk, emphasizing ethical considerations.Design advanced scenario-based financial models using generative AI for strategic decision-making.Target Personas:1. Financial Analysts: Professionals wanting to incorporate AI-driven insights into financial modeling.2. Risk Managers: Individuals focusing on improving risk assessment techniques using GenAI tools.3. Investment Advisors: Advisors seeking to leverage GenAI for better portfolio management and scenario analysis.4. Tech-Savvy Accountants: Accountants eager to use AI to automate financial reporting and analysis processes.5. Finance Students: Learners seeking hands-on experience with the latest technologies in financial modeling.
Overview
Section 1: Generative AI Overview
Lecture 1 Course Intro Video
Lecture 2 Introduction and Welcome
Lecture 3 Generative AI Fundamentals
Lecture 4 Generative AI vs Traditional AI
Lecture 5 Prompt Engineering Fundamentals
Section 2: Financial Modelling Overview
Lecture 6 Financial Modeling 101
Lecture 7 Key Steps in Financial Modeling and AI’s Role
Lecture 8 Generative AI and Financial Data
Section 3: Tools for financial Modelling
Lecture 9 Tools Overview - ChatGPT, Copilot, and More
Lecture 10 Limitations and Challenges of GenAI Tools
Lecture 11 Factors and Framework to Choose the Right Tool Based on Your Needs
Lecture 12 Conclusion and Summary
Section 4: Predictive Modeling Basics
Lecture 13 Introduction and Welcome
Lecture 14 Introduction to Predictive Modeling
Lecture 15 Generative AI for Prediction
Lecture 16 Predicting Revenue & Expense Growth
Section 5: Advanced Tools and Techniques
Lecture 17 Introduction to Advanced Gen AI Tools
Lecture 18 DataRobot in Action
Lecture 19 Evaluating Model Accuracy
Section 6: Real-World Applications
Lecture 20 Use Case - Investment Portfolio optimization
Lecture 21 Creating Expense Budgets with AI Based on Business Model and Revenue Predictions
Lecture 22 Creating Decision Tables and Dashboards for Visualizing Outputs from Financial M
Lecture 23 Conclusion and Summary
Section 7: Assumption Building
Lecture 24 Introduction and Welcome
Lecture 25 Market Research and Creating Assumptions
Lecture 26 Expenses Assumptions from Revenue Drivers
Lecture 27 Building Input Templates and Metrics
Section 8: Detailed Financial Forecasting
Lecture 28 Predicting Revenue with Detailed Segmentation
Lecture 29 Analyzing Expense Patterns
Lecture 30 Building Cash Flow and calculating IRR
Section 9: Case Study Application
Lecture 31 Scenario and Sensitivity Analysis to Highlight Risks in the Hotel Budget Model
Lecture 32 Other Type of Financial Models
Lecture 33 Wrap up of Hotel Financial Modelling
Lecture 34 Conclusion and Summary Video
Section 10: Advanced Optimization
Lecture 35 Introduction
Lecture 36 Advanced AI Techniques for Financial Optimization
Lecture 37 Reinforcement Learning for Dynamic Decision-Making
Lecture 38 Integrating AI Techniques
Section 11: Advanced Forecasting
Lecture 39 Advanced Forecasting Techniques with AI
Lecture 40 Applying Advanced Forecasting Techniques to Real-World Applications of Forecasti
Lecture 41 Refining and continuously Improving Models
Section 12: Future Trends in AI
Lecture 42 Trends in Financial AI Applications
Lecture 43 Leveraging AI for Regulatory Compliance in Financial Modeling
Lecture 44 Review of Key Concepts and Roadmap for Applying AI Strategies
Lecture 45 Conclusion and Summary
Lecture 46 Course Outro Video
This course targets financial analysts, risk managers, investment advisors, tech-savvy accountants, and finance students, offering tools to integrate GenAI into modeling, enhance risk assessment, automate reporting, and explore advanced financial technologies.