Your decision
Where can preparation and reconciliation improve while preserving reproducibility and accountable sign-off?
Resources & evaluation
GENELLIPSE FOR ENTERPRISE
Actuarial & insurance leaders
Connect operational information, approved analysis, and professional judgement.
THE DECISION BEHIND THE TECHNOLOGY
Can you reproduce the result and defend the judgment behind it?
Actuarial value depends on the relationship between data, assumptions, methods, uncertainty, and professional judgment. Automation should reduce avoidable preparation while making those relationships easier to inspect. It should not hide methodology choices behind a convincing narrative.
Explore the decision and evidence flow
Select a stage to inspect its owner, evidence, and stopping condition.
CONTROLLED PROGRESSION
Reconcile the basis
Confirm cohort, period basis, gross or net treatment, currency, and treatment of adjustments before analysis.
- Accountable owner
- Actuarial data owner
- Evidence to retain
- Control totals · basis definition · reconciled snapshot
- Stop or escalate when
- Do not compare outputs whose underlying bases differ without a documented bridge.
ILLUSTRATIVE BUSINESS CONTEXT
Illustrative review: two reserve runs differ. The team first separates exposure changes, claims development, data corrections, assumption revisions, and model changes. AI can help organize supporting evidence and draft commentary; the qualified reviewer decides whether the explanation and financial conclusion are appropriate.
Your discussion checklist
Use these prompts with your team. Checked items are a local working aid, not a readiness certification; they reset when you leave this guide.
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Plan the evaluation around your decision
Use this guide to align the right stakeholders before a demonstration or MVP.
Where Genellipse helps
Bring AegisNow, GeneData, and Cortex AI together for a bounded reserving, reinsurance, or insurance workflow. GeneAnalytics can support movement and portfolio analysis.
What to evaluate
Source reconciliation, model and assumption versions, exception handling, explanation quality, and evidence retained for review.
Evidence to request
A reviewed historical comparison, reproducible run, reconciliation record, movement analysis, and a named approval owner.
A useful first engagement
Choose one portfolio and reporting cycle. Measure preparation and review effort together with quality and traceability.
Choose a use case without weakening professional control
Start where preparation and reconciliation create a material bottleneck. The evaluation should preserve the distinction between data assistance, calculation, interpretation, and formal sign-off.
Reserving and reporting
Evaluate one portfolio over an agreed reporting cycle. Reconcile movements to source, retain method and assumption versions, and compare both preparation and review effort. Test corrections after the reporting cutoff.
Reinsurance reconciliation
Link treaty terms, policy or claim allocations, recoverables, adjustments, and settlement status. Separate a calculated receivable from an agreed counterparty balance and an actual cash settlement.
Pricing and experience analysis
Define cohort, observation window, exposure basis, and treatment of sparse data. Evaluate stability and representativeness, with qualified review of methodology and customer implications.
Define what AI may assist and what professionals must decide
Generated text should not become an authoritative calculation or opinion merely because it reads well. Specify boundaries at the task level.
Appropriate assistance to assess
Evidence assembly, document comparison, exception grouping, and draft movement commentary may be useful starting points. Test each against known cases and missing or contradictory information.
Authority to retain
Qualified owners approve methods, assumptions, materiality, overrides, and reporting conclusions. Record what the reviewer actually challenged rather than collecting a generic approval click.
Validation to preserve
Use an agreed historical comparison, sensitivity analysis, reproducibility checks, and independent challenge proportionate to the use. Track serious failures separately from average accuracy or time saved.