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Duration 14 hours (2 days)
Course Outline
Foundations of AI for Finance Experts
- Understanding AI and machine learning within the financial sector
- Overview of AI model types: classification, regression, and generative models
- Responsible AI: ensuring accuracy, transparency, and ethical practices in reporting
Automation of Financial Data Workflows
- Utilizing AI tools for data ingestion and extraction from PDFs and spreadsheets
- Data cleaning and transformation for analytical purposes
- Applying OCR, NLP, and LLMs to interpret unstructured financial text
AI-Powered Financial Statement Examination
- Automated ratio analysis and industry benchmarking
- Detecting trends and analyzing variances through machine learning
- Visualizing insights via AI-driven dashboards
Generative AI in Narrative Reporting
- Drafting executive summaries and variance comments using LLMs
- Developing management discussion & analysis (MD&A) with AI assistance
- Prompt engineering for effective financial storytelling and accuracy management
AI in Scenario Planning and Forecasting
- Basics of scenario modeling and simulation using ML
- Creating dynamic models for revenue, expense, and cash flow projections
- Conducting stress tests on financials under various macroeconomic conditions
Embedding AI in Current FP&A Processes
- Enhancing spreadsheet workflows with Python or AI plugins
- Automation and collaborative tools for monthly/quarterly closing processes
- Integrating AI into Excel, Power BI, or cloud-based FP&A platforms
Audit, Governance, and Internal Controls
- AI explainability and preparing for internal audits
- Recording assumptions and AI outputs to ensure compliance
- Establishing controls for AI-assisted financial reporting processes
Conclusion and Future Directions
Requirements
- Understanding of core financial statements and key performance indicators
- Proficiency with spreadsheets or fundamental data management tools
- Basic knowledge of Python or a readiness to utilize AI-enhanced interfaces
Target Audience
- Corporate finance analysts
- FP&A teams
- Controllers
Testimonials (1)
The background / theory of LLMs, the exercise
