Assisted financial interpretation

How can you explain changes in profitability with AI without confusing calculations, findings and hypotheses?

1250 € per session, excl. VAT

In short

In a half-day session of 3 hours you use two financial years to identify significant changes, calculate the main ratios and draft a substantiated financial note. AI helps structure the commentary; calculations are checked separately and conclusions are submitted for professional validation.

Why this training?

An increase in turnover does not necessarily indicate improved profitability. Reading purchases, staff costs, depreciation and amortisation, and finance costs together helps identify the main factors behind changes in profit. AI can suggest convincing commentary while reversing a sign or inventing a cause. A usable analysis must link each finding to the accounts, distinguish hypotheses from facts and document the limitations of the available information. Case study used throughout: The fictitious organisation « Dorseline Agencement » reports rising turnover but declining operating profit. Using two annual profit and loss accounts and fictitious explanatory notes, participants must explain this discrepancy and prepare questions to put to the finance management team. Transfer to the workplace: At the next monthly review, reuse the framework with anonymised data in an authorised environment, recalculate the indicators and have the note reviewed by a qualified finance professional before using it for any decision-making.

Objectives of this training

  • Identify the line items and subtotals that determine profitability
  • Calculate absolute and relative changes and the selected ratios
  • Rank contributions to the change in operating profit
  • Distinguish numerical findings from explanations that still require confirmation
  • Draft and check an analysis note with AI assistance

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Operational managers required to comment on their financial results
  • Accounting staff and junior management controllers
  • Leaders of small organisations with basic accounting knowledge

Prior skills

  • Distinguish income, expenses, profit and cash.
  • Be able to perform simple calculations in a spreadsheet.
  • Have already formulated simple requests to generative AI.

What you will work on

  1. Ensure a reliable reading of the accounts

    Objective: Establish a comparable basis for the two financial years. Income, expenses, operating profit, financial result and net profit; units, signs, periods and changes in presentation.

  2. Measure significant variances

    Objective: Quantify changes that affect profitability. Variances in value and percentage terms; expenses as a proportion of turnover; operating margin; handling zero or negative baseline values.

  3. Build a substantiated interpretation

    Objective: Explain variances without going beyond the available evidence. Facts versus hypotheses; one-off events; limitations of price–volume explanations without additional data; distinction between profitability and cash.

  4. Check and present the diagnosis

    Objective: Finalise a note suitable for use in a financial review. Traceability of figures, consistency of conclusions, limitations and the human validation process.

What you take away

  • Comparative table of the two financial years with checked formulas
  • Table of contributions to the change in operating profit
  • One-page financial note distinguishing facts, hypotheses and questions
  • Completed checklist with anomalies corrected

Method and assessment

  • Short instructional inputs followed by immediate practice using the ongoing case study.
  • Individual work followed by work in pairs, with participants reviewing each other’s outputs.
  • Guided group discussion: what works, what needs correcting and what remains a human decision.
  • Preparation: Arrange a spreadsheet and access to generative AI authorised by the organisation. Consult the fictitious file provided; no raw confidential financial documents may be submitted to AI.

Observable criteria: Subtotals match the source data and variances are flagged. ; Changes and ratios are recalculated independently of AI, with denominators explicitly stated. ; The selected contributions explain the change in operating profit. ; Each finding refers to a quantified line item; no undocumented causal relationship is presented as certain. ; The note includes its limitations and the points requiring professional validation..

Frequently asked questions

Does AI perform the reference calculations?

No. The figures used come from verified formulas in the spreadsheet; every AI suggestion is checked.

Can we work with our own accounts?

Only using an anonymised version authorised by the organisation. The fictitious file is sufficient for all exercises.

Does this analysis allow conclusions to be drawn about the cash position?

No. The profit and loss account alone does not describe cash receipts, cash payments or financing needs.

Can the recommendations be applied automatically?

No. No sensitive decisions are automated; conclusions require validation by a qualified professional.

Last updated: