Actuarial work depends on more than running a model. Teams need reconciled data, approved methods, understandable movements and a clear record of judgement. A connected workflow makes it easier to establish what changed, why it changed and which evidence supports the final result.
01
Data preparation & reconciliation
Connect policy, claims and financial inputs to a controlled data snapshot. Record completeness checks, reconciliations and exceptions before the analysis begins.
02
Reserving workflows
Support a repeatable reserving cycle with versioned inputs, approved methods and recorded adjustments. Keep movement analysis and review evidence alongside the selected results.
03
Pricing analysis
Bring experience data, assumptions and scenario outputs into a reviewable pricing process. Compare changes on a consistent basis and document the rationale for the recommendation.
04
Valuation & capital analysis
Connect approved assumptions and model runs to the outputs needed by actuarial and finance stakeholders. Retain the evidence needed to explain changes between reporting periods.
05
Assumptions & model governance
Track the method, model version, parameter set and accountable owner for each run. Make changes and overrides visible to the people responsible for validation.
06
Commentary & review packs
Use AI assistance to assemble evidence and prepare draft explanations from approved material. Actuaries check the interpretation, resolve exceptions and approve the final communication.
YOUR BUSINESS AREA. A CONNECTED PLATFORM.
AegisNow
For actuarial
AegisNow supports actuarial modeling and review alongside insurance and reinsurance operations. GeneData can provide governed data preparation, while Cortex AI can assist with evidence assembly and draft commentary. Qualified actuarial owners retain responsibility for methods, assumptions, validation and sign-off.
Select a stage to see the action, accountable owner and evidence needed to move forward. This illustrative sequence is adapted to your business rules during scoping.
THE ACTION
Certify the inputs
Assemble the agreed reporting-period data and reconcile it to source totals. Resolve material exceptions or explicitly record their treatment.
Accountable ownerActuarial data owner
MEASURE THE CHANGE
Efficiency and control, assessed together.
Establish a baseline from your current process and agree targets before an evaluation. These measures define what to assess; they are not claims of achieved customer results.
Preparation & rerun effort
Time spent assembling a certified dataset and reproducing an analysis after an agreed change.
Review exceptions
Unresolved input, assumption, calculation and explanation issues at each review gate.
Reproducibility
Whether a reviewer can recreate an output from its retained data, methods, assumptions and model version.
A PRACTICAL STARTING POINT
Make the evaluation specific.
Start with a defined workflow, representative data and the people who approve the result. Confirm product configuration, integration requirements and delivery scope before wider adoption.
Explore the scope, practical considerations, and a useful starting point for your team.
Can our team retain existing actuarial models?
Yes, the evaluation starts with your approved methods, tooling and available interfaces. It establishes which preparation, execution and review steps can be connected without changing the accountable model owner or approved methodology.
What does AI contribute to the actuarial workflow?
AI can assist with preparation, evidence retrieval and draft explanations within the agreed scope. It does not replace actuarial judgement, validation or the professional responsibility for the final analysis.
