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Course Outline
Foundations of AI for Financial Professionals
- Understanding AI and machine learning within the financial sector
- Overview of AI model types: classification, regression, and generative models
- Responsible AI practices: ensuring accuracy, transparency, and ethical application in reporting
Automation of Financial Data Workflows
- Utilizing AI tools to ingest and extract data from PDFs and spreadsheets
- Data cleansing and transformation techniques for analytical readiness
- Applying OCR, NLP, and LLMs to decipher unstructured financial text
AI-Enhanced Financial Statement Evaluation
- Automated calculation of ratios and industry benchmarking
- Employing machine learning for trend identification and variance analysis
- Visualizing key insights through AI-driven dashboards
Generative AI in Narrative Reporting
- Drafting executive summaries and variance commentary using LLMs
- Assisting in the creation of Management Discussion & Analysis (MD&A) sections
- Prompt engineering strategies for financial storytelling and precision control
AI-Powered Scenario Planning and Forecasting
- Introduction to scenario modeling and simulation using ML
- Developing dynamic models for forecasting revenue, expenses, and cash flow
- Conducting stress tests on financials under various macroeconomic conditions
Integrating AI into FP&A Processes
- Enhancing spreadsheet workflows via Python or AI plugins
- Implementing collaborative tools and automation for monthly and quarterly closes
- Integrating AI into Excel, Power BI, or cloud-based FP&A platforms
Audit, Governance, and Control Frameworks
- Ensuring AI explainability and readiness for internal audits
- Documenting assumptions and AI outputs to meet compliance standards
- Establishing controls for AI-assisted processes in financial reporting
Recap and Future Pathways
Requirements
- Solid understanding of core financial statements and key performance indicators
- Proficiency with spreadsheets or fundamental data processing tools
- Basic familiarity with Python or readiness to utilize AI-driven interfaces
Target Audience
- Corporate finance analysts
- FP&A teams
- Controllers
14 Hours
Testimonials (1)
The background / theory of LLMs, the exercise
