Traceable financial controls

How can you use AI to produce financial control sheets that are verifiable and can actually be implemented?

1960 € per session, excl. VAT

In short

This seven-hour day, excluding breaks, enables participants to turn scattered financial procedures into a usable controls file. Generative AI assists with structuring and drafting, while participants verify sources, specify the evidence required and measure documentation quality before validation by a qualified professional.

Why this training?

A control described as ‘check the accounts’ specifies neither its scope, nor acceptable variances, nor the evidence to retain. This ambiguity undermines continuity of the closing process and makes reviewing the work more difficult. AI can harmonise descriptions and flag inconsistencies in documentation, but it can also invent a frequency or an approval. The training therefore requires every requirement to be linked to a source and decisions involving judgement to be referred to the finance lead. Ongoing case study: The fictitious organisation ‘Talvigne Composants’ is preparing its monthly close. Its controls over bank reconciliations, duplicate suppliers and the substantiation of manual journal entries are described in contradictory notes. Participants reconstruct three control sheets using entirely fictitious procedures, accounting extracts and evidence. Workplace application: Rework a closing control within your remit, using anonymised data and an authorised tool. Have the finance lead review the sheet, ask a colleague to test its execution, and track missing fields and requests for clarification.

Objectives of this training

  • Map the links between financial risks, controls and evidence
  • Draft three operational control sheets with supervised AI assistance
  • Distinguish sourced requirements from assumptions requiring validation
  • Test whether a control can be reproduced using its sheet
  • Measure the completeness and traceability of the file

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Accounting and finance managers overseeing closing controls
  • Internal control officers and internal auditors assessing financial documentation
  • Lead accountants responsible for formalising procedures

Prior skills

  • Know closing operations and the principles of internal financial control.
  • Be able to structure a request to generative AI and review its response.
  • Work with accounting extracts in a spreadsheet.

What you will work on

  1. Define the risks covered

    Objective: Link the three controls to closing risks. Control objective, accounting assertions, prevention and detection; distinction between procedure and evidence.

  2. Assess the sources

    Objective: Prepare an unambiguous, usable source collection. Versions, provenance, contradictions, anonymisation and limits on sharing with AI.

  3. Draft the sheets with AI assistance

    Objective: Produce three consistent operational descriptions. Structured instruction, mandatory references, executable steps, internal thresholds and segregation of duties.

  4. Define evidence and exceptions

    Objective: Make control results traceable. Evidence of execution, conclusion, variance, escalation, sign-off and retention in accordance with internal rules.

  5. Test through peer review

    Objective: Check that a third party can reproduce the control. Execution test, comparison against documents, ambiguities and the distinction between documentation quality and actual effectiveness.

  6. Measure and organise validation

    Objective: Finalise a file ready for professional review. Completeness indicators, traceability, reservations, version control and responsibilities for updates.

What you take away

  • Risk–control–evidence matrix
  • File containing three sourced control sheets
  • Log of assumptions, corrections and validations
  • Quality checklist and execution test report

Method and assessment

  • Brief instructional sessions followed by immediate practice on the ongoing case study.
  • Individual work followed by work in pairs, with peer review of the outputs.
  • Guided group discussion: what works, what needs correcting and what remains a human decision.
  • Preparation: Arrange access to an AI tool authorised by the organisation, without sharing confidential financial data. Identify a sheet template and documentation challenges; use only fictitious or anonymised examples.

Observable criteria: Each control covers an identified risk and refers to the source documents. ; Each sheet specifies the owner, frequency, scope, steps, evidence and handling of variances. ; No requirement invented by AI is presented as validated. ; A peer performs the tested control without undocumented verbal clarification. ; The percentages of completed fields and sourced requirements are calculated, with the remaining reservations recorded..

Frequently asked questions

Can AI validate a control?

No. It assists with drafting; validation is the responsibility of a qualified professional, with no automated sensitive decision-making.

Can real journal entries be used?

The exercises use fictitious or anonymised cases, exclusively within tools authorised by the organisation.

Does the file prove that the controls are effective?

No. Documentation quality is assessed; actual effectiveness requires tests on the operations concerned.

What retention period should be used?

Apply the internal rules; the applicable legal requirements must be checked with your legal department.

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