Introduction to Generative AI in Finance
- Overview of generative AI and its relevance to finance
- Key capabilities of Claude AI and Microsoft Copilot
- Benefits and limitations for financial professionals
- Ethical and regulatory considerations
Hands-on exercises
Getting Started with Claude AI
- Interface and core features
- Setting up and managing conversations
- Understanding context and memory
- Best practices for finance-related interactions
Hands-on exercises
Getting Started with Microsoft Copilot
- Integration with Microsoft 365 apps
- Using Copilot in Excel, Word, Outlook, and Teams
- Real-time assistance for financial tasks
- Collaboration and sharing insights
Hands-on exercises
Prompt Engineering for Finance
- Principles of effective prompting
- Crafting prompts for financial analysis
- Iterative refinement and follow-up questions
- Common pitfalls and how to avoid them
Hands-on exercises
Automating Financial Analysis and Reporting
- Extracting and summarizing financial data
- Generating variance analysis and commentary
- Automating recurring reports
- Ensuring accuracy and consistency
Hands-on exercises
AI for Budgeting and Forecasting
- Assisting with budget preparation
- Scenario analysis and sensitivity testing
- Forecasting trends and anomalies
- Integrating AI outputs into planning models
Hands-on exercises
Risk Assessment and Compliance Support
- Identifying financial risks with AI
- Monitoring compliance and regulatory updates
- Generating risk reports and summaries
- Audit support and documentation
Hands-on exercises
Enhancing Financial Narratives and Communication
- Drafting executive summaries and insights
- Creating clear and concise financial stories
- Tailoring communication for stakeholders
- Using AI to improve presentation content
Hands-on exercises
Integrating AI into Financial Workflows
- Embedding AI into daily finance tasks
- Combining Claude AI and Copilot for efficiency
- Automating data entry and reconciliation
- Monitoring and optimizing AI usage
Hands-on exercises
Ethics, Privacy, and Governance in AI Adoption
- Data privacy and confidentiality
- Bias and fairness in AI outputs
- Governance frameworks for AI in finance
- Building trust and transparency
Hands-on exercises
Capstone Application and Best Practices
- Review of key concepts and techniques
- Applying AI to a comprehensive finance scenario
- Sharing best practices and lessons learned
- Planning for continued learning and adoption
Hands-on exercises