Top 10 Best Insurance Modeling Software of 2026

AXIS by Moody's Analytics is a premier actuarial modeling platform tailored for the insurance industry, supporting deterministic and stochastic projections for life, annuities, health, property & casualty, and pensions. It excels in asset-liability management (ALM), economic capital modeling, pricing, reserving, and regulatory reporting under frameworks like IFRS 17, LDTI, and Solvency II. With its open architecture and powerful Syntex scripting language, AXIS enables highly customizable, scalable models trusted by the world's largest insurers for strategic decision-making.

Prophet, developed by FIS (fisglobal.com), is a leading actuarial modeling software platform tailored for the insurance industry, particularly for life insurance, pensions, and annuities. It enables precise stochastic and deterministic modeling, cash flow projections, asset-liability management, and regulatory compliance calculations such as Solvency II and IFRS 17. With its flexible scripting language and extensive library of pre-built models, Prophet supports complex product development and scenario analysis for enterprise-scale operations.

MoSes (Modeling Software for Enterprise Solutions) by Milliman is a comprehensive actuarial modeling platform tailored for the insurance industry, enabling deterministic and stochastic projections for life insurance, annuities, pensions, and health products. It supports complex financial reporting, risk management, asset-liability modeling, and regulatory compliance such as IFRS 17, LDTI, and ORSA. The software excels in handling enterprise-scale computations with high accuracy and integrates seamlessly with other Milliman tools for end-to-end actuarial workflows.

Emblem by FIS Global is a sophisticated stochastic modeling platform tailored for life insurance companies, enabling actuaries to perform asset-liability management, risk assessment, and scenario analysis. It supports complex calculations for product pricing, capital adequacy, and regulatory compliance such as IFRS 17 and LDTI. Integrated within FIS's broader financial services ecosystem, it facilitates seamless data flow and enterprise-wide insights.

Igloo by Milliman is a cloud-native actuarial modeling platform tailored for the insurance industry, supporting deterministic and stochastic modeling for pricing, reserving, asset-liability management, and risk assessment across life, health, and P&C lines. It leverages Milliman's proprietary data and tools, such as loss cost monitors and predictive models, to deliver accurate financial projections and scenario analyses. Designed for enterprise-scale operations, Igloo enables collaborative model development and seamless integration with enterprise systems.

PolySystems by Verisk is a comprehensive actuarial modeling platform designed for insurance companies to perform stochastic simulations, pricing, reserving, and capital modeling across life, health, P&C, and annuity products. It leverages Verisk's extensive data ecosystem, including catastrophe models, to deliver precise risk assessments and financial projections. The software excels in handling complex, multi-line insurance portfolios with high computational efficiency.

SAS Viya is a cloud-native analytics platform designed for advanced statistical modeling, machine learning, and AI, widely used in insurance for actuarial modeling, risk pricing, reserving, and claims analytics. It provides tools like SAS Visual Analytics, Viya ML, and specialized procedures for GLMs, survival analysis, and credibility theory tailored to insurance needs. The platform supports scalable processing of massive datasets and integrates with insurance-specific data sources for end-to-end model development and deployment.

@RISK by Lumivero is a Monte Carlo simulation add-in for Microsoft Excel designed for quantitative risk analysis and modeling uncertainty. In insurance applications, it enables actuaries and risk managers to simulate complex scenarios such as claims reserving, premium pricing, catastrophe losses, and solvency assessments using probabilistic distributions. The software supports correlations, sensitivity analysis, and tornado charts to identify key risk drivers within familiar Excel workflows.

Oracle Crystal Ball is an Excel-based Monte Carlo simulation and risk analysis tool that allows users to model uncertainty by assigning probability distributions to variables and running thousands of simulations for probabilistic forecasting. In insurance modeling, it excels at stochastic processes like loss reserving, premium pricing scenarios, and capital requirement assessments under regulatory frameworks such as Solvency II. It integrates seamlessly with spreadsheets for scenario analysis, sensitivity testing, and optimization, making it a staple for actuarial risk quantification.

MATLAB is a high-level numerical computing environment and programming language developed by MathWorks, ideal for matrix manipulations, data analysis, visualization, and algorithm development. In insurance modeling, it supports stochastic simulations, risk assessment, actuarial calculations, and predictive analytics through specialized toolboxes like the Financial Toolbox, Statistics and Machine Learning Toolbox, and Econometrics Toolbox. While highly flexible for custom models such as loss reserving, pricing, and capital modeling, it requires scripting expertise and lacks native insurance-specific workflows compared to dedicated actuarial software.