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Actuarial Modeling Software for Insurance Companies

Actuarial software and insurance modeling software compared: four platforms for pricing, reserving and IFRS 17 and LDTI work, rated on seven criteria.

15 min read 3 vendors evaluated Updated November 2026

Key Takeaways

  • ›WTW ResQ leads this evaluation, ahead of 2 other assessed platforms.
  • ›WTW ResQ is aimed at p&C insurers and reinsurers requiring loss reserving with emphasis on regulatory compliance and capital management.
  • ›FIS Prophet suits growth-stage insurers prioritizing modern architecture and integration flexibility.
  • ›Core Modeling Engine carries the most weight in this evaluation, at 25% of the total.
  • ›Watch for this: Don't underestimate integration complexity.
  • ›In the evaluation: Test platform performance with your actual portfolio data during proof-of-concept.
At a Glance

Actuarial Modeling Software for Insurance Companies: Vendors Compared

3 platforms, assessed against the criteria in this guide. The positions are our opinion — here is how we evaluate.

Vendor names link to the full profile further down the page; where we also list the vendor, “Directory” opens its entry.
VendorPositionBest for
WTW ResQDirectory profile ›LeaderP&C insurers and reinsurers requiring loss reserving with emphasis on regulatory compliance and capital management.
FIS ProphetDirectory profile ›Strong ContenderGrowth-stage insurers prioritizing modern architecture and integration flexibility.
Milliman AriusStrong ContenderP&C insurers requiring loss reserving capabilities with regulatory compliance for property and casualty lines.
Section 1

Executive Summary

By 2025, insurers using advanced actuarial modeling platforms reduced product launch timelines while improving capital efficiency.

Actuarial modeling software is the insurance modeling software actuaries use to quantify risk, set premiums and produce the projections that reporting standards such as IFRS 17 and LDTI require. This guide compares four actuarial platforms on seven weighted criteria, led by the core modeling engine, regulatory compliance and integration with insurance data.

Spreadsheet-based modeling becomes hard to control at enterprise scale, which is why the evaluation also weighs performance, scalability and model validation.

Current platforms offer automated model validation, integrated regulatory reporting, collaborative modeling with version control, and integration with core insurance systems, which is meant to reduce manual data handling and reconciliation for actuarial teams.


Section 2

Why Actuarial Modeling Software Matters Now

The convergence of regulatory complexity, competitive pressure, and technological advancement has transformed actuarial modeling from a back-office function to a strategic competitive advantage.

Modern actuarial platforms enable rapid product innovation and dynamic pricing strategies that were previously impossible with legacy tools. Leading carriers now perform daily pricing adjustments based on real-time market data, competitive intelligence, and emerging risk factors. This agility proves particularly valuable in volatile markets where traditional annual pricing cycles create competitive disadvantages.

The integration of machine learning and advanced analytics into actuarial workflows represents a fundamental shift in how insurers approach risk assessment and capital management. Platforms that combine traditional actuarial modeling with predictive analytics enable more sophisticated risk segmentation, dynamic reserving, and proactive portfolio management strategies that drive measurable improvements in combined ratios and return on equity.

The COVID-19 pandemic and subsequent economic volatility highlighted the critical importance of robust actuarial modeling capabilities. Insurers with advanced scenario modeling and stress testing capabilities weathered market disruptions more effectively, maintaining regulatory capital ratios while competitors struggled with outdated assumptions and manual recalibration processes.


Section 3

Build vs. Buy Analysis

The complexity of modern actuarial modeling requirements, combined with the specialized expertise needed for insurance mathematics and regulatory compliance, strongly favors commercial solutions over in-house development. Building actuarial software requires deep domain expertise in insurance mathematics, regulatory frameworks across multiple jurisdictions, and sophisticated financial modeling capabilities that few organizations possess internally.

Historical attempts at custom actuarial platform development have consistently exceeded budgets and timelines, with typical overruns due to underestimated complexity in areas like stochastic modeling, nested simulation capabilities, and regulatory reporting automation. The ongoing maintenance burden for custom actuarial solutions proves particularly challenging as regulatory requirements evolve and new mathematical techniques emerge.

DimensionBuild In-HouseBuy Commercial
Development TimelineLonger: everything is built and validated in-houseShorter: the platform exists; configuration, data and integration remain
Actuarial Expertise RequiredA large team of specialized actuarial and technology roles2-3 power users
Regulatory ComplianceFull responsibilityVendor-supported
Feature EvolutionInternal roadmap onlyIndustry-driven innovation
Risk ProfileHigh technical/regulatoryLow operational risk

Section 4

Key Capabilities & Evaluation Criteria

Actuarial modeling platforms must balance mathematical sophistication with operational efficiency, supporting complex insurance calculations while maintaining performance across large portfolios. The evaluation framework should prioritize core actuarial functions while assessing integration capabilities, scalability, and regulatory compliance support.

Modern platforms distinguish themselves through advanced capabilities like distributed computing for nested simulations, automated model validation workflows, and native support for emerging standards like IFRS 17 and LDTI. The ability to handle both traditional deterministic modeling and sophisticated stochastic simulations within a unified environment becomes increasingly critical as product complexity grows.

Capability DomainWeightWhat to Evaluate
Core Modeling Engine25%Stochastic capabilities, nested simulation performance, mathematical accuracy, Monte Carlo efficiency
Regulatory Compliance20%IFRS 17/GAAP support, Solvency II, regulatory reporting automation, audit trail completeness
Integration & Data15%Policy administration connectivity, data warehouse integration, real-time data feeds, API completeness
Performance & Scalability15%Calculation speed, portfolio size limits, parallel processing, cloud-native architecture
User Experience10%Modeling workflow efficiency, collaboration features, version control, dashboard capabilities
Model Validation10%Automated testing, sensitivity analysis, back-testing capabilities, documentation generation
Deployment Options5%Cloud/on-premise flexibility, security standards, disaster recovery, multi-tenancy support
💡
Evaluation Tip
Test platform performance with your actual portfolio data during proof-of-concept. Synthetic test datasets often mask scalability limitations that emerge with real-world complexity.

Section 5

Vendor Landscape

The actuarial modeling software market features established players with decades of insurance expertise alongside emerging cloud-native platforms that emphasize modern architecture and user experience. Traditional vendors like Moody's Analytics and Willis Towers Watson maintain strong positions through deep actuarial knowledge and comprehensive regulatory support, while newer entrants focus on deployment speed and integration capabilities.

Market consolidation has accelerated as insurance technology investments increase, with major acquisitions reshaping the competitive landscape. The distinction between pure actuarial modeling platforms and broader insurance analytics suites continues to blur as vendors expand their capabilities to address end-to-end actuarial workflows.

WTW ResQ

Leader
Strengths: Choose it when the reserving is P&C. It is a specialist loss reserving system, regulatory compliance support includes Solvency II and ORSA requirements, and model validation and documentation features come with audit trail capabilities.
Considerations: Check the user experience. The user interface requires modernization next to newer platforms, and integration capabilities lag the pure-play technology vendors.

FIS Prophet

Strong Contender
Strengths: Choose it when calculation speed and integration matter more than regulatory templates. The calculation engine is high-performance and scales for large portfolios, the architecture is modern and cloud-native with integration capabilities and flexible deployment options, and life insurance modeling comes with growing P&C functionality.
Considerations: It needs shaping. Complex product structures require significant customization.

Milliman Arius

Strong Contender
Strengths: Choose it when the book is P&C and Schedule P is due. P&C actuarial expertise is deep with reserving capabilities, and regulatory reporting covers P&C requirements including Schedule P.
Considerations: It is a P&C reserving tool. Life insurance capabilities are limited next to the P&C side, and integration with modern policy administration systems is challenging.
⚠️
Common Pitfall
Don't underestimate integration complexity. Many projects exceed timeline and budget due to data quality issues and policy system connectivity challenges that surface during implementation.

Section 6

Pricing & Total Cost of Ownership

Actuarial modeling software pricing varies significantly based on deployment model, user count, and modeling complexity. Enterprise platforms typically require substantial upfront investment but offer better unit economics at scale, while cloud-based solutions provide lower entry barriers with subscription-based pricing that scales with usage.

Hidden costs often exceed initial license fees, particularly for data integration, model migration, and specialized consulting services. Regulatory compliance modules, advanced analytics features, and multi-jurisdiction support frequently carry premium pricing that can double base platform costs.

VendorLicense ModelKey Cost Drivers
WTW ResQPerpetual + MaintenanceLine of business, jurisdiction licenses, user tiers
FIS ProphetSaaS SubscriptionPortfolio size, calculation volumes, integration APIs
Milliman AriusPerpetual + CloudP&C modules, catastrophe modeling, user licenses
3-Year TCO Estimation
TCO = (License × 3) + Implementation + (Maintenance × 3) + Data Integration + Training

Section 7

Implementation Roadmap

Actuarial modeling platform implementations require careful phasing to manage business continuity while enabling rapid value realization. Successful projects typically begin with pilot implementations on specific product lines before expanding to full portfolio coverage, allowing teams to develop expertise while minimizing operational risk.

The most critical success factor involves early engagement of both actuarial and IT teams to address data quality, integration requirements, and model validation protocols. Organizations that invest in comprehensive change management and training programs achieve faster time-to-value compared to technology-focused implementations.

Phase 1
Assessment & Design (Months 1–2)

Current state analysis, data quality assessment, integration architecture design, and model inventory. Define migration strategy and establish success metrics with stakeholder alignment.

Phase 2
Platform Setup & Integration (Months 3–5)

Software installation, environment configuration, data pipeline development, and core system integration. Initial model migration and validation framework establishment.

Phase 3
Pilot Implementation (Months 6–8)

Limited product line implementation with parallel running against existing systems. Model validation, user training, and workflow optimization with iterative refinement.

Phase 4
Portfolio Expansion (Months 9–12)

Rollout to additional product lines and business units. Advanced feature deployment, regulatory reporting automation, and performance optimization across full portfolio.

Phase 5
Optimization & Governance (Months 13–15)

Advanced analytics deployment, model governance framework implementation, and continuous improvement processes. Center of excellence establishment and knowledge transfer completion.


Section 8

Selection Checklist & RFP Questions

This comprehensive evaluation checklist addresses the critical decision points and technical requirements for actuarial modeling platform selection. Use this framework to ensure thorough vendor assessment and successful implementation planning.


Section 9

Related Resources

◆ Spotlight

This position is available to vendors in this category for $499 a year. Labeled as paid. It does not affect this guide's evaluation. Sponsor this guide

Frequently Asked Questions

What are the key differences between traditional and cloud-based actuarial platforms?

Cloud-based platforms offer faster deployment, automatic updates, and better integration capabilities, while traditional on-premise solutions provide more customization options and data control. Modern cloud platforms increasingly match traditional capabilities while offering superior scalability.

Which actuarial modeling platform is best for IFRS 17 compliance?

Several platforms in this guide support IFRS 17 work. Platform selection should align with your specific product portfolio and regulatory jurisdiction requirements.

How do I evaluate actuarial modeling software performance requirements?

Test platforms with your actual portfolio data during proof-of-concept, focusing on calculation speed, memory utilization, and scalability under realistic conditions. Synthetic test data often masks performance limitations that emerge with real-world complexity and volume.

Methodology

How We Evaluate

Weighted evaluation criteria
Core Modeling Engine
Regulatory Compliance
Integration & Data
Performance & Scalability
User Experience
Model Validation
Deployment Options

Bars are scaled to the heaviest criterion. The percentages are the real weights and add up to 100%.

We write these guides for people running a software selection. This one covers 3 platforms and should save you weeks of research, but it will not replace your own reference calls and a proof of concept.

We review vendors' websites, product documentation and press releases, along with regulatory texts and other publicly available information. Our assessments are our opinion. No vendor supplied them and nobody audited them. Use them to build a shortlist, then go and test it yourself.

The criteria weights are ours as well. We chose them for this category and publish them so you can see what we valued, and weight things differently if your situation calls for it.

No vendor pays to appear in this guide or to be described the way it is. Spotlight placements alongside our guides are paid and labeled as paid placements, and they change nothing about the evaluation.

Last reviewed November 2026. Enterprise software moves quickly and pricing is negotiated rather than listed, so parts of this will age. If we have something wrong, tell us and we will fix it. That goes double if you work for a vendor we cover.

Tags:actuarial modeling softwareinsurance actuarial systemsIFRS 17 compliancestochastic modelinginsurance risk management