GITNUXSOFTWARE REVIEW
Business FinanceTop 10 Best Actuarial Software of 2026
Editorial shortlist comparing actuarial software options like Milliman Integrate, FIS Prophet, and PolySystems for pricing, workflows, and fit.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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Milliman Integrate is the best overall pick for actuarial teams that need governed, repeatable calculation execution across valuation cycles because its orchestration standardizes how runs are run and reduces uncontrolled changes between cycles, while PolySystems is the stronger fit for groups wanting study governance around versioned model builds and less manual rework when assumptions change.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Milliman Integrate
Run orchestration with governance controls that standardize calculation execution across teams and cycles.
Best for: Fits when actuarial teams need governed, repeatable workflows with strong integration into upstream and downstream systems.
FIS Prophet
Editor pickModel execution control that supports governed, repeatable batch valuation across actuarial cycles.
Best for: Fits when actuarial teams need governed projection runs that produce reserve, valuation, and scenario outputs on schedule.
PolySystems
Editor pickStudy governance around versioned model builds and repeatable execution runs, reducing manual rework between assumption changes and projection outputs.
Best for: Fits when actuarial teams need repeatable projection studies with controlled governance and automation for batch execution.
Comparison Table
Milliman Integrate
enterpriseCloud-based actuarial modeling software for insurance projections and analysis.
Run orchestration with governance controls that standardize calculation execution across teams and cycles.
Milliman Integrate fits teams that run recurring actuarial work and need operational control over how inputs, model code, and outputs move through a workflow. Configurable job execution helps standardize steps across experience studies, liability modeling, and valuation handoffs into reporting. Integrations focus on connecting external data sources and consuming outputs in structured forms rather than relying on manual exports.
A key tradeoff is governance discipline. Controlled workflows reduce ad hoc model tinkering, so teams must invest in run configuration management and change review before shifting assumptions or code. It works best when a single actuarial team or a program of teams shares standardized pipelines for quarterly and annual valuation cycles.
- +Workflow automation supports repeatable actuarial runs across valuation cycles
- +Governance-oriented execution reduces uncontrolled changes between runs
- +Integration points support moving inputs and outputs without manual file juggling
- +Configuration management supports standardized processing steps by program
- –Workflow governance requires disciplined setup for assumption and execution changes
- –Complex pipeline configuration can slow down rapid prototyping
- –Tooling depth favors model ops teams over purely desktop users
- –External system connectivity depends on existing data interface design
Actuarial valuation operations teams
Quarterly valuation runs with controlled execution
Consistent results across cycles
Model governance teams
Change-managed model execution workflows
Reduced run-to-run drift
Show 2 more scenarios
Actuarial reporting teams
Feeding regulatory reporting outputs
Faster reporting handoffs
Routes calculation outputs into downstream reporting steps with standardized processing.
Enterprise systems integration teams
Connecting data sources and destinations
Lower manual data movement
Connects external input and output systems into automated job runs.
Best for: Fits when actuarial teams need governed, repeatable workflows with strong integration into upstream and downstream systems.
FIS Prophet
enterpriseActuarial modeling platform for insurance valuation, reporting, and risk analysis.
Model execution control that supports governed, repeatable batch valuation across actuarial cycles.
FIS Prophet performs actuarial projection and valuation workflows for insurance and reinsurance models.
It centers on model build, assumption management, and cash flow outputs designed for repeatable reserve and capital runs.
Prophet’s differentiator is tight integration with FIS data and model execution controls that support governed batch execution across actuarial cycles.
- +Production-grade batch execution for repeated actuarial valuation cycles
- +Strong scenario and sensitivity output generation for assumption testing
- +Governance-oriented controls for model execution in shared environments
- +Clear separation of model logic and assumptions for controlled reruns
- –Less flexible for ad hoc analysis outside managed model runs
- –Workflow configuration can require specialized actuarial engineering discipline
- –Integration depth varies by surrounding data and reporting stack
- –Model changes may increase retesting effort across dependent scenarios
Reserving actuaries
Rerun projections after assumption updates
Comparable outputs with documented deltas
Actuarial model reviewers
Trace assumption and output differences
Clear reviewable change history
Best for: Fits when actuarial teams need governed projection runs that produce reserve, valuation, and scenario outputs on schedule.
PolySystems
vertical specialistActuarial software for insurance valuation, pricing, projections, and financial reporting.
Study governance around versioned model builds and repeatable execution runs, reducing manual rework between assumption changes and projection outputs.
PolySystems is an actuarial modeling solution focused on repeatable projection workflows and model management across life and non-life use cases. The product is built around configurable calculation logic, assumption handling, and scenario runs used for valuation-style outputs.
PolySystems adds operational control through study governance features and repeatable model builds, rather than only desktop calculation. Its differentiator for model teams is integration and automation support that reduces manual rework between assumption updates and projection outputs.
- +Configurable calculation workflows support consistent projection runs
- +Model governance features help control versioned study execution
- +Automation reduces handoffs between assumptions and output packages
- +Server-friendly design suits scheduled batch actuarial runs
- –Workflow setup can take time for teams used to desktop tools
- –Model customization depth depends on available templates and configuration
- –Integration requires careful mapping between external data and study inputs
- –Advanced reporting layouts can need additional work beyond core outputs
Actuarial leads
Maintain traceable assumption governance
Reviewable results with lineage
Reserving actuaries
Rerun projections for assumption testing
Documented assumption impact
Show 1 more scenario
Underwriting and actuarial teams
Assess cohort profitability patterns
Evidence for pricing follow-ups
Produces portfolio and cohort valuation outputs for investigating underwriting profitability drivers.
Best for: Fits when actuarial teams need repeatable projection studies with controlled governance and automation for batch execution.
Aon PathWise
enterpriseActuarial projection platform for life insurance, retirement, and risk modeling.
Model release and governance workflow that ties valuation logic, assumption changes, and review steps into controlled promotions.
Aon PathWise is an actuarial workflow and model governance solution tailored to insurer and reinsurer use cases where modeling tasks must be coordinated across teams.
- +Strong model governance workflow for coordinating actuarial changes
- +Controlled promotion of valuation runs reduces rework during cycles
- +Reusable actuarial artifacts support consistent assumption application
- +Designed for multi-team delivery with review and audit trails
- –Not positioned as a desktop modeling tool for one-off analyses
- –Implementation requires discipline to keep configuration and assumptions consistent
- –Automation depth depends on how model tasks are modularized upfront
- –Limited fit for teams needing deep custom programming flexibility
Actuarial model governance teams
Coordinate valuation work across teams
Aligned assumption and logic releases
Reserving actuaries
Test reserve assumptions with reruns
Comparable projection results
Show 1 more scenario
Model documentation reviewers
Maintain audit-ready model documentation
Audit-ready model artifacts
Keeps controlled releases and documentation tied to valuation cycles for consistent governance.
Best for: Fits when insurers need coordinated actuarial model governance across valuation cycles.
Akur8
vertical specialistTransparent machine learning software for insurance pricing and actuarial modeling.
Versioned publishing of assumption sets with traceable change history across valuation workflows.
Akur8 is actuarial software focused on assumption and model governance workflows for valuation and regulatory processes. It provides a structured way to manage assumption sets and track model changes across runs, with configurable export steps for downstream calculations.
- +Versioned assumption set management supports repeatable valuation runs.
- +Controlled publishing reduces the risk of mixing inputs across scenarios.
- +Workflow configuration supports multi-team model governance patterns.
- +Exports can be aligned to downstream actuarial engines and reporting steps.
- –Governance workflow depth can require staff training to use correctly.
- –Limited built-in actuarial calculation coverage compared with full modeling engines.
- –Scenario generation tooling is narrower than dedicated stochastic stacks.
- –Complex setups may slow initial onboarding without clear administration practices.
Actuarial leads
Track changes to assumption sets
Reproducible valuation baselines
Actuarial model reviewers
Review output differences by version
Clear change history for outputs
Show 1 more scenario
Regulatory reporting teams
Export governed configurations downstream
Consistent outputs across cycles
Runs structured export steps so regulatory-style workflows can repeat the same assumption inputs.
Best for: Fits when actuarial teams need governed, versioned assumption workflows and controlled publishing for valuation runs.
ALFA
enterpriseActuarial and financial modeling software for general insurance pricing and reserving.
Assumption management and run configuration are designed to keep projection inputs consistent across iterations.
ALFA is structured to support full actuarial projection lifecycles, including assumption management and repeatable run configurations. The software is commonly used by actuarial teams that must produce the same projection inputs across multiple studies and reporting cycles, which is a higher bar than desktop-style calculators. Model governance typically shows up as enforced workflow steps and centralized configuration, which supports reviewability during validation and change management cycles.
- +Assumption-centric workflow reduces input drift across model versions
- +Configurable run structure supports consistent deterministic and stochastic studies
- +Standardized execution order improves reviewability of projection outputs
- +Well-suited for recurring actuarial cycles across product lines
- –Upfront configuration work slows first setup for new use cases
- –Complex study designs may require stronger internal modeling discipline
- –Tighter workflow structure can limit rapid ad hoc experimentation
- –Model building often depends on established team practices
Actuarial valuation teams
Quarterly reserving model reruns
Fewer input inconsistencies
Solvency modeling teams
Scenario generation for capital modeling
More consistent scenario results
Show 2 more scenarios
Experience study owners
Assumption updates from experience
Faster controlled assumption refresh
Apply updated experience-driven inputs to projection builds without changing downstream model logic each cycle.
Model governance groups
Model change and validation workflow
Improved change traceability
Use standardized study structures to make changes traceable and easier to validate across model releases.
Best for: Fits when actuaries need repeatable projection studies with strong assumption control and governed run workflows.
SLOPE
vertical specialistCloud-based actuarial modeling and projection platform for insurers.
Workbook-driven actuarial workflow execution with traceable run inputs for controlled projection and valuation output consistency.
SLOPE is built around workflow execution that ties inputs, calculation steps, and outputs into a repeatable run configuration. It supports scenario generation for cash flow projection and includes batch-style execution patterns that reduce manual reruns of valuation and reserve work. Model governance is handled through execution control, versioning of run configurations, and structured capture of changes that affect outputs.
- +Configurable workflow execution reduces manual reruns for valuation cycles
- +Scenario generation supports both deterministic and stochastic projection runs
- +Run configuration traceability helps tie outputs to specific inputs
- +Batch execution supports higher throughput for repeated model runs
- –Workflow packaging can limit freeform spreadsheet-style model edits
- –Advanced customization may require deeper process mapping
- –Complex dependency handling can add overhead for one-off analyses
- –Integration work may be needed to fit existing actuarial toolchains
Actuarial reserving teams
Monthly reserve projections with scenario control
Faster, auditable reserve cycles
Capital modeling teams
Stochastic capital sensitivity runs
More repeatable capital outputs
Show 1 more scenario
Model governance leads
Change control across valuation assumptions
Lower governance friction
Maintains structured run configurations so output changes map to input changes.
Best for: Fits when actuarial teams need governed, repeatable projection runs with controlled scenario sets.
XSG
vertical specialistEconomic scenario generator for actuarial modeling and risk assessment.
Model run traceability that ties assumptions and model components to released output packages for repeatable governance cycles.
XSG from Deloitte targets actuarial model production and governance with an implementation framework designed around enterprise delivery. The core workflow centers on structured model building, scenario and projection execution, and controlled release of outputs for valuation and regulatory-style reporting.
- +Centralized governance workflow for model components and run artifacts
- +Scenario execution designed for repeated projection and output consistency
- +Model lifecycle controls support controlled releases into downstream reporting
- +Enterprise deployment orientation fits teams running multiple concurrent models
- –Heavier implementation effort than lighter desktop actuarial tools
- –Limited evidence of end-user customization without structured model workflows
- –Assumption changes may require disciplined coordination to keep traceability intact
- –Integration depth depends on surrounding Deloitte delivery and data setup
Actuarial production teams
Execute scenario projections in batch
Reliable batch valuation outputs
Model governance and auditors
Verify traceable assumptions and artifacts
Audit-ready traceability
Show 1 more scenario
Reserving actuaries
Re-run projections after changes
Documented reserve deltas
Re-executes projection workflows so reserve differences are captured with tracked run artifacts.
Best for: Fits when large actuarial teams need controlled model lifecycle, repeatable projections, and governance for production runs.
Moody’s AXIS
enterpriseInsurance actuarial modeling software for life, health, and annuity projections.
Production-grade actuarial model execution with controlled configuration for repeatable valuation cycles.
Moody’s AXIS is positioned for actuarial modeling and recurring valuation-style workloads inside a Moody’s Analytics ecosystem.
- +Model runs stay repeatable through configurable workflows and controlled inputs
- +Strong integration path for Moody’s Analytics driven actuarial and risk workflows
- +Scenario generation and assumption refresh fit recurring valuation cycles
- +Governance tooling supports audit-style control for production model changes
- –Admin setup and role design require disciplined governance for production use
- –Modeling workflows can feel less flexible than fully custom desktop actuarial setups
- –Some advanced modeling choices depend on how workloads are packaged in AXIS modules
- –Integrations outside the Moody’s Analytics ecosystem may require extra engineering effort
Actuarial analysts
Repeat valuation runs across cycles
Repeatable valuation results
Model governance teams
Control audit-ready production workflows
Audit-ready actuarial workflows
Show 1 more scenario
Reserving actuaries
Assess reserve assumption impacts
Quantified reserve effects
Updates assumptions and reruns configured projections to measure reserve changes across valuation cycles.
Best for: Fits when actuarial teams need recurring valuation execution with strong governance and Moody’s analytics integration.
Atlas
vertical specialistActuarial modeling software focused on stochastic scenario generation and analysis.
Study configuration that parameterizes scenario runs across assumption sets and captures consistent outputs for comparison.
Atlas coordinates stochastic actuarial runs for pricing and liability modeling by driving scenario generation, executing model batches, and packaging outputs.
- +Reusable study configurations standardize repeated stochastic runs
- +Structured outputs make batch results easier to compare across scenarios
- +Assumption management supports driver-level variation without rewriting models
- +Batch run orchestration fits iterative modeling cycles
- –Less coverage for deterministic modeling workflows than stochastic-first users expect
- –Governance and audit controls feel lighter than enterprise model risk teams need
- –Integration depth depends on export and import patterns rather than native API breadth
- –UI navigation can slow down for large scenario libraries
Pricing actuaries
Run scenario-based pricing studies
Comparable pricing scenarios
Liability modeling teams
Package stochastic liability outputs
Actionable batch results
Show 1 more scenario
Actuarial model reviewers
Review assumption-driven study changes
Traceable study history
Keeps study configuration tied to run artifacts so assumption changes can be traced for review.
Best for: Fits when actuarial teams run repeated stochastic pricing or liability projections and need controlled batch configuration.
Conclusion
After evaluating 10 actuarial software, Milliman Integrate stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Frequently Asked Questions About Actuarial Software
How do ALFA and Milliman Integrate keep assumption inputs consistent across repeatable projection runs?
Which tools in the list run actuarial workflows without reauthoring calculations for every model run?
When is it better to choose Akur8 or Aon PathWise for assumption governance and controlled publishing?
What breaks if an organization skips run orchestration governance in Milliman Integrate or XSG?
How do Atlas and SLOPE differ for stochastic modeling and scenario generation workflows?
How should integration and API requirements be handled when connecting actuarial workflows to upstream data and downstream reporting?
Which tool is more suitable for cash flow projection production when workflows must be scheduled and repeatable?
How do ALFA and Akur8 support audit-oriented model governance without turning every run into a manual checklist?
What integration or administration capabilities matter most when deploying Moody’s AXIS versus server-based options like XSG?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
How to Choose the Right Actuarial Software
In actuarial software, the biggest differences show up in how well the workflow handles inputs and outputs for your model run, how it tracks assumptions, and how it lets you rerun changes without manual rework—especially around data import, assumption versioning, and output audit trails.
Data import with field-level validation
Why it matters
Data import with field-level validation reduces the chance that bad exposures, policy attributes, or experience extracts silently distort results. For actuarial software, this protects the run before assumptions and projections ever matter.
How to check
Ask for a demo using a sample dataset with intentional formatting issues (missing values, wrong date formats, mismatched IDs). Verify whether the system flags issues before processing and shows which fields triggered the error.
Assumption version control and reuse
Why it matters
Assumption version control matters because actuaries routinely rerun models with small changes and need traceability across versions. Without it, results become hard to explain and replicate months later.
How to check
During a demo, change a single assumption (then revert) and confirm the system preserves a version history you can browse. Ask how the model run ties a result to the exact assumption set that produced it.
Scenario setup and rerun workflow
Why it matters
A scenario setup and rerun workflow matters when you compare alternative experience, assumptions, or sensitivity variants without rebuilding everything. Actuarial work depends on consistent reruns to keep comparisons meaningful.
How to check
Request a walkthrough where they define two scenarios and rerun with the second scenario using minimal clicks. Confirm whether the output shows scenario parameters and whether the rerun reuses the same base inputs.
Output reporting and result traceability
Why it matters
Output reporting and result traceability helps stakeholders inspect what changed and why. In actuarial software, you need outputs that link back to the model run inputs and assumptions without spreadsheet stitching.
How to check
Ask to export results and also view the in-app report for the same run. Check whether the report includes run identifiers and key input summaries, not just tables of numbers.
Automation and API surface for runs
Why it matters
Automation and API surface matters when teams run the same modeling workflow repeatedly across datasets or with scheduled processes. Better API depth reduces manual steps and keeps outputs consistent across reruns.
How to check
In the demo, ask whether you can trigger a run programmatically and retrieve outputs automatically. Request to see documentation or an example script for creating a run configuration and collecting results.
Audit log and provenance for changes
Why it matters
Audit log and provenance for changes matter because actuarial deliverables often require post-hoc explanation. When the system records who changed what and when, it reduces time spent reconstructing model history.
How to check
Perform a small workflow change (import data, update an assumption, rerun) and ask the system to show an audit trail. Verify that the log includes user/time stamps and connects changes to the resulting outputs.
Red flags
- Exports that lack any link from results back to run inputs
- Assumptions change without clear version history or rollback
- Data issues are corrected silently instead of flagged before a run
Fit by situation
- If your team repeats the same model runs across multiple datasets, prioritize Data import with field-level validation.
- If you expect frequent assumption tweaks and reruns, prioritize Assumption version control and reuse.
- If you need to compare multiple variants without rebuilding, prioritize Scenario setup and rerun workflow.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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