Actuarial Tables & Models
Buy and sell actuarial tables & models data. Risk tables and mortality/morbidity data that power pricing models. Custom actuarial data is extremely scarce.
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Find Me This Data →Overview
What Is Actuarial Tables & Models Data?
Actuarial tables and models are the foundational datasets that power risk assessment, pricing, and regulatory compliance across insurance and financial services. These datasets encompass mortality/morbidity tables, risk models, and predictive analytics frameworks used by insurers, pension funds, and financial institutions to quantify and price complex risks. The actuarial modeling software market—which depends on robust actuarial data—grew from USD 588.67 million in 2024 to USD 626.11 million in 2025, with projections reaching USD 993.44 million by 2030, reflecting strong demand for data-driven risk solutions. Custom actuarial data is extremely scarce and highly valued. Organizations leverage actuarial tables for life insurance modeling, health insurance pricing, property & casualty underwriting, pension planning, and reinsurance calculations. The market is segmented by functionality (claims analysis, data integration, financial forecasting, predictive analytics, pricing & underwriting, risk assessment, and regulatory compliance) and spans life insurance, health insurance, P&C, reinsurance, and pension/retirement planning sectors. Key market drivers include the need for real-time data analysis, cloud-based model deployment, AI-driven predictive analytics, and customizable risk frameworks. Major players include Moody's Analytics, Milliman, Willis Towers Watson, FIS Global, SAP SE, Oracle, SAS Institute, and IBM, among others.
Market Data
USD 2.18 billion
Global Actuarial Modeling Software Market (2025)
Source: 360iResearch
USD 3.46 billion
Projected Market Size (2032)
Source: 360iResearch
6.81%
CAGR (2026–2032)
Source: 360iResearch
USD 4.7 billion
North America Market Value (2025)
Source: HTF Market Intelligence
15.50%
North America CAGR (2025–2033)
Source: HTF Market Intelligence
Who Uses This Data
What AI models do with it.do with it.
Insurance Companies
Life, health, and P&C insurers use actuarial tables for premium pricing, claims analysis, risk assessment, and regulatory compliance reporting.
Pension & Retirement Plan Administrators
Pension funds and retirement plan operators rely on mortality and morbidity models for liability valuation, benefit calculations, and fund forecasting.
Reinsurers & Risk Managers
Reinsurance firms and enterprise risk management teams leverage actuarial models for portfolio optimization, catastrophic risk modeling, and real-time trigger-based payouts.
Banks & Financial Services
Financial institutions use actuarial models for credit risk assessment, financial forecasting, and regulatory capital calculations.
What Can You Earn?
What it's worth.worth.
Single User Access
$3,600
Individual analyst or researcher license
Corporate User Access
$5,800
Multi-user enterprise deployment
Excel Data Sheet
$1,800
Downloadable actuarial data in spreadsheet format
Market Research Reports
€3,185 / $3,545 / £2,778
Comprehensive software market analysis with 122+ pages
What Buyers Expect
What makes it valuable.valuable.
Accuracy & Validation
Actuarial tables must be rigorously validated against real-world claims, mortality, and morbidity experience; buyers verify data lineage and statistical methodology.
Regulatory Compliance
Data must align with local regulatory frameworks (SOX, GDPR, insurance capital standards) and support compliance reporting in claims analysis, risk assessment, and underwriting functions.
Customization & Segmentation
Buyers require tables segmented by age, gender, health status, geographic region, and product type; custom actuarial models tailored to specific insurance portfolios command premium pricing.
Real-Time & Predictive Capability
Modern buyers increasingly demand models supporting real-time data analysis, AI-driven predictive analytics, and cloud-based deployment for faster, trigger-based decision-making.
Documentation & Metadata
Comprehensive documentation on data sources, calculation methodologies, confidence intervals, and update frequency is essential for institutional buyers.
Companies Active Here
Who's buying.buying.
Develops and deploys actuarial modeling software; launched enhanced predictive analytics for insurance companies in June 2024.
Major player in actuarial consulting and software; partnered with Moody's Analytics on predictive analytics tools and provides custom actuarial modeling services.
Global consulting and software firm offering actuarial models for insurance, risk management, and pension planning.
Provides risk assessment, data integration, and financial forecasting software for insurance and banking sectors.
Supplies predictive analytics and data integration platforms used for actuarial modeling and risk assessment across insurance and finance.
FAQ
Common questions.questions.
What is the difference between actuarial tables and actuarial modeling software?
Actuarial tables are the underlying risk datasets (mortality, morbidity, claims experience) that power pricing and valuation. Actuarial modeling software is the platform that ingests, processes, and applies these tables to generate pricing models, forecasts, and risk assessments. Both are complementary; buyers of custom actuarial data often feed it into modeling software.
How do I price custom actuarial data?
Pricing varies based on data complexity, customization level, and buyer size. Standard market research reports range from $1,800 to $5,800+ depending on access tier (single user, corporate, Excel download). Custom actuarial models—particularly those tailored to specific insurance lines, geographies, or health cohorts—are extremely scarce and typically command negotiated, premium pricing well above standardized tiers.
Who are the primary buyers of actuarial data?
Primary buyers include insurance companies (life, health, P&C), reinsurers, pension plan administrators, banks, and risk management firms. Within these organizations, actuaries, pricing teams, and enterprise risk managers are the key decision-makers. Consulting firms like Deloitte, PwC, and KPMG also purchase and resell actuarial data to clients.
What data quality standards should I meet?
Buyers expect rigorous statistical validation, clear documentation of data sources and methodologies, regulatory compliance (SOX, GDPR, insurance capital standards), segmentation by demographic and geographic factors, and metadata on confidence intervals and update frequency. Custom data with AI-driven predictive capability and real-time update capability commands higher premiums.
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