Analyzing and writing reports

How to analyze financial data and write reports with generative AI?

  • ChatGPT
  • Claude
  • Microsoft Copilot

1960 € per session, excl. VAT

In short

This training is for finance and management control professionals. Participants use various generative AI tools to analyze financial data, draft reporting comments, and organize rigorous checks. They leave with a commented report and a control grid, enhancing the clarity and reliability of their decision-making analyses.

Why this training?

The problem
Financial teams struggle to effectively analyze large volumes of data and write clear, reliable reports.
What it costs today
This leads to superficial analyses, imprecise reporting commentaries, and decisions made on fragile foundations.
Why this skill
This skill is necessary to quickly transform raw data into actionable insights and validate their reliability for decision-making.
What you gain
Participants and the company gain in analysis quality, autonomy in report generation, and reliability of the financial information produced.

Objectives of this training

  • Clarify the structuring information of financial data (columns, units, periods, calculation rules).
  • Explore financial datasets to identify budget, actuals, and significant trends.
  • Transform complex financial results into a clear summary note for decision-makers.
  • Document the sources, assumptions, and investigation points of financial analyses.
  • Test the robustness of analyses by identifying calculation errors or hasty conclusions.
  • Define a process for human validation and traceability for generated reports.

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Financial managers who analyze performance
  • Management controllers who develop budgets
  • Accountants who prepare financial summaries
  • Financial analysts who write reports

Prior skills

  • AI Fundamentals and AI Prompting completed, or equivalent experience (a learning prerequisite, not a registration condition).
  • Understanding of key financial indicators of the company
  • Knowledge of existing reporting systems
  • Ability to identify relevant data
  • Proficiency in data manipulation tools (e.g., spreadsheets)
  • A paid subscription to an AI solution offering the features used, the organisation’s authorisation for third-party tools, and the actual accounts and access rights.

To prepare before the session

  • A computer per participant with the necessary software installed.
  • Access to the selected generative AI tools, with verified licenses and authorizations.
  • A specific business case to work on or acceptance to work on fictitious data.

What you will work on

  1. Prepare Reliable Data

    This block ensures the quality and consistency of data before any analysis.

  2. Analyze Variances

    This block enables the identification and examination of differences between forecasts and financial reality.

  3. Draft Management Commentary

    This block enables the formulation of clear and relevant summaries from analyses.

  4. Organize Controls

    This block enables the establishment of mechanisms to validate the reliability and compliance of reports.

What you take away

  • An annotated report based on fictitious data.
  • A variance analysis prepared during the session.
  • A customized control grid.
  • An action plan for applying the methods.

Method and assessment

  • Demonstrations with explanations using a concrete case
  • Guided exercises followed by application to your role
  • Peer review of results and source verification
  • An individual or team action plan

Assessment is formative: participants complete and review a practical case linked to the intended deliverable (An annotated report using fictional data, a variance analysis and a review checklist). Criteria include meeting the brief, accuracy, checks performed and the ability to explain decisions. Each participant identifies an application to test in their own work.

Frequently asked questions

What will be the concrete outcome for my team after this session?

Your team will be able to produce faster and more relevant financial analyses using generative AI tools. They will write clear and controlled reporting commentaries, improving the company's decision-making basis.

Who should attend this session and what are the prerequisites for effective participation?

Financial managers, management controllers, and analysts are ideal participants. A good understanding of financial indicators and reporting systems is required, along with proficiency in data manipulation tools.

What data and documents are used during the exercise, and how is our information protected?

We use fictitious or anonymized data for practical exercises. Confidentiality is ensured as no sensitive company data from your organization is required or processed during the training.

What type of practical exercise is conducted during the session?

Participants work on a simulated business case. They analyze a fictitious financial dataset to identify trends, calculate variances, and write a complete, annotated report, using AI tools like ChatGPT, Claude, or Microsoft Copilot.

What are the limitations of AI for this task and how is the validity of the results ensured?

Generative AI tools such as ChatGPT, Claude, or Microsoft Copilot are powerful assistants, but their output must be validated by a human expert. The session emphasizes defining a process for human validation and traceability for generated reports.

How can this session be adapted to the specificities of our business or our concrete cases?

Although the exercise is based on a fictitious case, the methods and tools learned are universal. The personalized action plan developed at the end of the session allows for direct application of the concepts to your specific professional contexts, using your organization's data.

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