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Course Outline
Foundations of AI for Finance Professionals
- Understanding AI and machine learning within the financial landscape
- Overview of AI model types: classification, regression, and generative models
- Responsible AI practices: ensuring accuracy, transparency, and ethical use in reporting
Automation of Financial Data Processing
- Employing AI tools for data ingestion and extraction from PDFs and spreadsheets
- Data cleaning and transformation techniques for analytical readiness
- Applying OCR, NLP, and LLMs to interpret unstructured financial text
AI-Enhanced Financial Statement Analysis
- Automating ratio analysis and industry benchmarking
- Identifying trends and conducting variance analysis via machine learning
- Visualizing key insights through AI-driven dashboards
Generative AI for Narrative Reporting
- Drafting executive summaries and variance commentary using LLMs
- Developing Management Discussion & Analysis (MD&A) sections with AI assistance
- Prompt engineering techniques for precise financial storytelling and accuracy control
AI-Powered Scenario Planning and Forecasting
- Introduction to scenario modeling and simulation using ML
- Constructing dynamic models for revenue, expense, and cash flow forecasts
- Stress-testing financial projections under various macroeconomic assumptions
Integrating AI into Established FP&A Workflows
- Enhancing spreadsheet workflows with Python or AI-powered plugins
- Utilizing collaborative tools and automation to streamline monthly and quarterly closes
- Embedding AI capabilities into Excel, Power BI, or cloud-based FP&A platforms
Audit, Governance, and Internal Controls
- Ensuring AI explainability and readiness for internal audits
- Documenting assumptions and AI outputs to meet compliance requirements
- Establishing robust controls for AI-assisted processes in financial reporting
Course Summary and Strategic Next Steps
Requirements
- Proficiency with core financial statements and key performance metrics
- Practical experience with spreadsheets or foundational data analysis tools
- Familiarity with Python or a readiness to adopt AI-enhanced interfaces
Target Audience
- Corporate finance analysts
- Financial Planning & Analysis (FP&A) teams
- Controllers
14 Hours
Testimonials (1)
The background / theory of LLMs, the exercise
