Applied AI for Financial Statement Analysis & Reporting Training Course
Applied AI introduces new levels of efficiency and intelligence to the way finance professionals analyse and report on business performance.
This instructor-led, live training (online or onsite) is aimed at intermediate-level finance professionals who wish to integrate AI tools into their financial statement workflows to enhance accuracy, automate repetitive tasks, and gain forward-looking insights.
By the end of this training, participants will be able to:
- Automate data extraction from financial documents using AI tools.
- Apply machine learning models to analyse trends and anomalies in financial statements.
- Use generative AI to assist in variance commentary, narrative reports, and scenario simulation.
- Interpret AI-generated outputs responsibly in the context of finance reporting and planning.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customisation Options
- To request a customised training for this course, please contact us to arrange.
Course Outline
AI Foundations for Financial Professionals
- What is AI and machine learning in the context of finance
- Types of AI models: classification, regression, generative models
- Responsible AI: accuracy, transparency, and ethical use in reporting
Automating Financial Data Processing
- Using AI tools for data ingestion and extraction from PDFs and spreadsheets
- Cleaning and transforming data for analysis
- Leveraging OCR, NLP, and LLMs to interpret unstructured financial text
AI-Driven Financial Statement Analysis
- Automated ratio analysis and benchmarking
- Trend detection and variance analysis using machine learning
- Visualising insights using AI-powered dashboards
Generative AI for Narrative Reporting
- Using LLMs to draft executive summaries and variance commentary
- Creating management discussion & analysis (MD&A) with AI support
- Prompt engineering for financial storytelling and accuracy control
Scenario Planning and Forecasting with AI
- Introduction to scenario modelling and simulation with ML
- Building dynamic models for revenue, expense, and cash flow forecasting
- Stress testing financials under macroeconomic assumptions
Integrating AI into Existing FP&A Workflows
- Augmenting spreadsheet workflows with Python or AI plugins
- Collaborative tools and automation for monthly/quarterly closes
- Embedding AI into Excel, Power BI, or cloud FP&A platforms
Audit, Governance, and Internal Controls
- AI explainability and internal audit readiness
- Documenting assumptions and AI outputs for compliance
- Setting controls for AI-assisted processes in financial reporting
Summary and Next Steps
Requirements
- Familiarity with key financial statements and metrics
- Experience using spreadsheets or basic data tools
- Some exposure to Python or willingness to use AI-enhanced interfaces
Audience
- Corporate finance analysts
- FP&A teams
- Controllers
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Testimonials (1)
The background / theory of LLMs, the exercise
Joanne Wong - IPG HK Limited
Course - Applied AI for Financial Statement Analysis & Reporting
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