Own Every Solution with Nice Engine.
Build your in-house actuarial modeling capabilities on a Python-based platform
your team and preferred partners can extend.
Nice Engine provides an established Python-based foundation on which your organization can build faster.
It brings together the core components your team needs.
Architecture
A flexible, open architecture for your models, data, cloud, and integrations.
Base Functionality
Mortality and insurance product implementations, user interfaces, data management, governance and reports.
Workflows
Established tools and processes to support your business operations and development.
Training
Comprehensive onboarding program, documentation, and test suites to help you build with confidence.
Accelerator to an in-house build
AI is shifting the actuarial modeling economics towards in-house builds. Nice Engine gives you the strategic advantages of an internal build, while reducing the cost and risk of building a modeling platform from scratch.
Control your development priorities, work with your preferred partners, and tailor modeling capabilities to your business.
Build from Scratch
Longer time to production
18-24+ months*
Higher total cost
Large multi-year investment
Higher execution risk
Many moving parts,
more dependencies
Key person risk
Knowledge concentrated
in a small number of specialists
Ongoing maintenance burden
Continuous technology and functionality R&D
Slower adaptation
High architecture uncertainty
and independent technology
research costs.
Build on Nice Engine
Faster path to production
6-12 months*
Lower total cost
Avoid recreating core platform capabilities
Lower execution risk
Proven foundation with established processes and controls
Vendor expertise
Onboarding focused on knowledge transfer to your team
Sustainable and scalable
Vendor supported functionality and technology updates
Faster adaptation
Extend capabilities on a proven, performant, and maintainable
architecture.
Build from Scratch
Build on Nice Engine
Longer time to production
18-24+ months*
Faster path to production
6-12 months*
Higher total cost
Large multi-year investment
Lower total cost
Avoid recreating core platform capabilities
Higher execution risk
Many moving parts,
more dependencies
Lower execution risk
Proven foundation with established processes and controls
Key person risk
Knowledge concentrated
in a small number of specialists
Vendor expertise
Onboarding focused on knowledge transfer to your team
Ongoing maintenance burden
Continuous technology and functionality R&D
Sustainable and scalable
Vendor supported functionality and technology updates
Slower adaptation
High architecture uncertainty
and independent technology
research costs.
Faster adaptation
Extend capabilities on a proven, performant, and maintainable
architecture.
*Internal implementation estimates based on comparable project scope, staffing, migration, and training assumptions. Actual timing, cost, and risk depend on the project.
Build with the team you choose.
Develop with your internal team or preferred consulting partners,
with Nice Engine supporting the underlying platform.
- Develop company-specific capabilities
- Build internal knowledge through onboarding
- Maintain control over your development priorities
- Accelerate development with practical agentic AI
A shared foundation.
A partnership that lasts.
Nice provides
- Platform foundation
- Onboarding & knowledge transfer
- Platform maintenance & upgrades
- Product support
Your team & partners develop
- Company-specific product features,
- analytical capabilities, and process
- integrations.
Implementation scope and support are defined for each engagement.
Frequently Asked Questions
Can Nice Engine work with our existing systems?
Yes. Nice Engine is designed to fit into your existing actuarial environment. It can exchange data with financial models, databases, Excel, reporting tools, and other systems that support programmatic integration. Most insurers already have financial models and processes they want to keep, so Nice Engine can be introduced where it adds the most value rather than requiring a wholesale replacement.
How do we govern code changes?
Your organization determines who can modify the model. Model developers can work with the Python source code, while pricing or valuation users can use controlled interfaces without code access. Changes can be version-controlled through Git and tools such as Azure DevOps, with pull requests, automated testing, deployment pipelines, and a complete history of model changes.
Do all users need to know Python?
No. Pricers can work through familiar interfaces such as Excel to manage inputs, define sensitivities, run processes, and review results. Python access is available to model developers who want to extend or customize the platform, but it is not required for day-to-day pricing work. Clients can also create custom interfaces and process integrations to fit their preferred pricing workflow.
Explore what you could build on Nice Engine.
Let’s discuss your modeling goals and development needs.