Documented and prioritised risks

How can you turn scattered incidents and obligations into a usable, traceable and revisable register?

1960 € per session, excl. VAT

In short

A seven-hour day, excluding breaks, to structure a register of legal and compliance risks using generative AI. Participants identify scenarios, document their sources, calibrate their risk ratings and organise risk treatment. The result is checked before any business use and submitted for validation by a qualified professional.

Why this training?

An inventory of concerns is not enough to manage risks: causes, unwanted events and consequences are often confused. Without an owner or justification for the ratings, priorities become difficult to defend. AI can help extract and rephrase scenarios, but it can also invent an obligation or overestimate a control. The approach therefore requires identifiable sources, explicit assumptions and human validation of the judgements made. Continuing case study: The fictitious organisation « Néracime Distribution » outsources its order preparation. Complaints, incomplete contracts and access permissions that have not been reviewed form a fictitious case file. Management requests a register covering contractual risks, confidentiality and monitoring of the service provider’s commitments. Transfer to the workplace: Within an authorised real-world scope, apply the framework with the compliance manager, have the ratings validated and organise an initial review. Compare the completeness of the register before and after correction, without sharing confidential documents unless authorised.

Objectives of this training

  • Define the scope and mandatory fields of the register.
  • Formulate scenarios that distinguish between causes, events and consequences.
  • Justify inherent and residual risk ratings.
  • Assign a treatment and an owner to each priority risk.
  • Measure the completeness, traceability and consistency of the register.

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Legal, compliance and internal control managers.
  • Process owners who contribute to risk mapping.

Prior skills

  • Know the processes and controls within your area of work.
  • Be able to formulate a request to generative AI and verify its response.
  • Use filters and simple formulae in a spreadsheet.

What you will work on

  1. Defining the register’s scope

    Objective: Establish the scope and rules of use. Processes covered, exclusions, categories, confidentiality and validation responsibilities.

  2. Extracting traceable scenarios

    Objective: Distinguish between facts, assumptions and risks. Assisted extraction, document references, cause-event-consequence formulation; obligations to verify with your legal department.

  3. Structuring the rows

    Objective: Eliminate ambiguities and duplicates. Stable identifier, category, owner, existing controls, evidence and status.

  4. Calibrating the ratings

    Objective: Make priorities explainable. Ordinal likelihood and impact scales, inherent risk, demonstrated effectiveness of controls and residual risk.

  5. Organising risk treatment

    Objective: Link priorities to actions. Treatment options, owner, deadline, evidence of implementation and risk acceptance authority.

  6. Checking and preparing the review

    Objective: Assess quality and maintain the register. Completeness, traceability, consistency of scores, version control and events that trigger a revision.

What you take away

  • Completed register with identifiers, sources, ratings, controls and owners.
  • Field dictionary and rating scale with explanatory notes.
  • Prioritised risk treatment plan with deadlines and expected evidence.
  • Quality control checklist and review protocol.

Method and assessment

  • Short input sessions followed by immediate practice using the continuing case study.
  • Individual work followed by work in pairs, with peer review of the outputs.
  • Facilitated group discussion: what works, what needs correcting and what remains a human decision.
  • Preparation: Identify a scope and useful document categories without bringing sensitive data. Check access to AI and spreadsheet tools authorised by the organisation; a fictitious case file is provided.

Observable criteria: Each scenario distinguishes between cause, event and consequence, with no unjustified duplicates. ; Each row includes a source or an explicitly identified assumption. ; Ratings follow the scale; any reduction to residual risk is based on a documented control. ; Each priority risk has an owner, an action and a deadline. ; The percentage of mandatory fields completed and consistency anomalies are calculated..

Frequently asked questions

Can AI decide on priorities?

No. It proposes analyses; no sensitive decisions are automated.

Can we use our contracts?

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

Are the ratings objective?

They remain judgements governed by a rating scale; their justifications and uncertainties must be retained.

Can the register be used immediately?

It provides an operational foundation that must be validated by a qualified professional before actual use.

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