Actuarial assumption change tracking
Changes to assumptions are difficult to explain when input data and model versions are stored separately.
The challenge behind the workflow.
Changes to assumptions are difficult to explain when input data and model versions are stored separately.
Connect long-duration policy, premium, claims, and actuarial information while retaining historical meaning. Focus on reproducible assumptions, clear customer context, and handoffs between operations, finance, and actuarial teams.
Data to bring together
- Assumption tables
- Model run metadata
- Experience study outputs
Source systems are examples of the data required. Confirm connector availability, permitted access, refresh timing, and the authoritative owner before implementation.
How Genedata supports the work.
Configure one connected workflow, then reuse its mappings, definitions, and review process as the business grows.
- 01
Connect and prepare
Associate each assumption set with its source evidence, owner, and effective date.
Build the preparation as a reusable visual workflow or reviewed code, with explicit source mappings and validation checks. - 02
Investigate and validate
Compare approved versions and identify the portfolios affected by a proposed change.
Keep shared definitions and source versions with the analysis so another team can reproduce the result. - 03
Publish and review
Publish a review pack linking changes, evidence, and model run references.
Make the output available to the right people with appropriate access, ownership, and review evidence.
An assumption change record
Make the next run easier.
A shared version history reduces manual reconstruction during actuarial and finance reviews.
Start from one approved example. Save the agreed mappings and definitions, publish the reviewed output, and let the next team follow the same evidence instead of rebuilding the preparation.
Measure your own improvement
Time to trace an assumption to supporting evidence
Record a baseline before the pilot and compare like-for-like work afterward. Results depend on source quality, configuration, and adoption.Review and responsibility
A designated actuarial authority approves assumption changes before production use.
AI with professional judgment.
Use AI to organize documents and explain analytical changes. Underwriting, benefit eligibility, and actuarial assumptions need qualified human review.
Try the workflow with your team.
Use representative, approved sample data. Agree the expected output and a review owner before extending the workflow to a live process.