Insurance
AI-ready analytics for insurers facing faster markets and stricter regulators
Climate volatility, real-time pricing, and evolving fraud patterns demand analytics that legacy tools can't deliver. Posit Team gives actuaries, underwriters, and data scientists the governed R and Python platform to build, validate, and deploy models with the audit trails and reproducibility that NAIC, GLBA, GDPR, and HIPAA require.
Gen Re: Automating underwriting for 230 data scientists across five countries
Gen Re's global team uses Posit to cut underwriting processing time from 30 minutes to 5 minutes per submission, saving 600 hours per day while maintaining data residency compliance across North America, Europe, and Africa.
Develop and iterate in your environment
Work in the IDE you prefer like RStudio, VS Code, JupyterLab, or Positron. Access data wherever it lives, manage reproducible environments with renv or conda, and publish interactive Shiny, Streamlit, or Dash applications for fast stakeholder feedback.
Govern with confidence
Maintain control of your data science infrastructure with SAML/OIDC SSO, validated package repos, role-based access controls, and audit logs exportable to your SIEM. Meet compliance needs for NAIC Model Laws, GLBA, GDPR, CCPA, HIPPA, and FCRA from a single admin interface built for regulated environments. Deploy on-premises, in your VPC, or on managed Kubernetes. Use Quarto to generate documented, reproducible actuarial model outputs with integrated narratives, automated calculations, and full provenance for rate filings and regulatory review.
Reduce cost and complexity
Consolidate fragmented replace high-cost MATLAB and Excel-based actuarial workflows with a single governed platform built on open source R and Python. Right-size compute resources, keep your code portable, and if you ever move on, your work comes with you.
Proven results
Measurable outcomes at insurance companies
Data science teams at insurers and reinsurers ship faster, automate manual processes, and give underwriters and pricing teams direct access to the analysis behind their decisions.
Scaling Bayesian models in insurance
We're building out our Posit Workbench and Team deployment now... You can run Python, you can serve Python models from there, you can serve our R models from there."
— Kevin Dalton, Senior Data Scientist, Great American Insurance
Production-ready model deployment
Recently we implemented proper deployment release management for all our models so nothing goes to production without going through the deployment."
— Mythili Krishnaraj, Global Delivery Lead Pricing and Analytics Platform, AXA XL
More precise pricing models
Generali integrated demand, contract duration, and price sensitivity data to build more competitive pricing methodologies.
Self-serve underwriting analytics
The Hartford's data science team deployed interactive applications on Posit Connect that let underwriters run sophisticated analyses independently, freeing data scientists for higher-value modeling work.
Featured resources
How Data Science is Revolutionizing Insurance
