IP Consulting — Actuariat · Modélisation
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    Solution · Documentation & regulatory review

    Define good. Then make the work pass.

    Turn actuarial and regulatory expertise into evidence rules, procedures, checks and stopping conditions that AI must follow. The report becomes a review interface, not an unsupported draft.

    The four controls of the actuarial documentation harness.

    Objective
    what must be delivered
    Evidence
    what may be used
    Procedure
    how the task runs
    Sign-off
    what humans approve
    The documentation risk

    The right-sounding source may still be the wrong source

    Why this matters

    Loading every regulation, policy, spreadsheet and prior report into one context creates distraction rather than control. A previous report can guide tone while being invalid evidence for a current-period fact.

    Good actuarial documentation depends on source eligibility, exact figures, applicable regulation, supported claims and clear handling of missing information.

    The model sees less—but what it sees is relevant, approved and tied to a defined purpose.
    The documentation harness

    Context controls what AI may use; procedure controls what it must do

    The control layer separates semantic retrieval from facts that require deterministic lookup.

    How the work runs
    01

    Register sources

    Classify regulation, company facts, quantitative data, methodology, narrative and reference-only material.

    02

    Build evidence packs

    Filter by entity, period, perimeter, jurisdiction and source eligibility before drafting starts.

    03

    Retrieve appropriately

    Use hybrid semantic retrieval for narrative, deterministic lookup for figures and exact references for regulation.

    04

    Draft through commands

    Run defined map, pack, draft, reconcile, review-claims and status procedures.

    05

    Reconcile claims

    Tie each material statement to its source, requirement and quantitative support.

    06

    Gate sign-off

    Prevent completion while evidence, reconciliation or reviewer decisions remain unresolved.

    Review interface

    Every finding stays attached to its basis

    A reviewer can move from report wording to requirement, source, remediation and decision without losing the chain.

    Reviewable evidence

    Claim ledger

    Material statements retain their source, support status and reviewer disposition.

    Figure reconciliation

    Period, unit, currency, perimeter and authoritative data source are checked deterministically.

    Missing-information flags

    The system identifies absent evidence rather than filling the gap with plausible language.

    Reader and control testing

    Acceptance conditions can include structure, readability, security and actuarial-specific checks.

    Claim boundary

    A 100% score means the defined checks passed

    It does not mean actuarial judgement disappeared, that every possible check was defined or that the report constitutes legal advice. Acceptance is deterministic only within the agreed standard.

    What this does not claim
    Source eligibility must be agreed with the document owner.
    Material judgements and unsupported claims are escalated to humans.
    The control set is versioned as requirements and reporting periods change.
    Typical deliverables

    What the documentation process leaves behind

    Engagement output
    Source and evidence-eligibility register
    Bounded evidence packs and retrieval layer
    Document-specific skills and command workflow
    Reconciled draft and quantitative checks
    Claim ledger and remediation list
    Reviewer decisions and sign-off package
    Questions before redesigning documentation

    How evidence and judgement stay separated

    Questions & boundaries
    Can the evidence set include internal and public sources?

    Yes. The important step is to declare which sources are eligible for each claim, version them and preserve the citation path. Confidential material remains inside the agreed environment.

    Does a 100% control score mean the report is compliant?

    No. It means the defined checks passed against the eligible evidence. Legal interpretation, completeness of the control set and material actuarial judgements remain outside that numeric claim.

    How is missing evidence handled?

    The process records a missing-information finding and routes it to an owner. It does not infer a supporting fact or fill the gap with plausible prose.

    Where should an implementation begin?

    Start with one recurring report, its authoritative sources, quantitative reconciliations and the acceptance conditions reviewers already apply. That creates a bounded standard before automation is introduced.

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    Related control patterns

    Browse all insights
    Solution · Actuarial model modernisation

    Move the model. Keep the evidence.

    Rebuild spreadsheet and legacy-platform models in Python while proving, step by step, that the original behaviour survived. AI accelerates construction; a deterministic harness decides whether it matches.

    Explore this solution    Solution · Controlled actuarial production

    Plain language in. Governed actuarial work out.

    Give actuarial teams a natural-language interface without turning production into a chat. Skills define the procedure, a harness executes and records it, and the approved engine performs the calculations.

    Explore this solution

    Where is documentation still assembled from open tabs, copied text and reviewer memory?

    Start with one report, its authoritative sources and the acceptance conditions the reviewer already applies.