ACT Collab

Actuarial Collaborative Technology

Actuarial modelling that works for your business

Python-powered solutions that combine the flexibility of modern technology with deep actuarial expertise

CaPytal Package

CaPytal is our flagship Python package for general insurance capital modelling and outwards reinsurance analytics. It provides a flexible, transparent framework that's intuitive for actuaries while being powerful enough for complex modelling tasks.

Simple Syntax, Powerful Models

CaPytal gives you the full power of Python's scientific computing ecosystem with a syntax designed specifically for actuarial workflows. The end code can all be writen in Python using your favorite IDE and development tools. Provides a comprehensive single package for all your modelling needs.

📊

Loss Simulation

Easily simulate aggregate or frequency severity loss distributions for insurance risk modelling

Intuitive syntax for complex distributions
Built-in parameter targeting
Controlled random seeding for recreatable and stable results

Simple Implementation

Generate loss distributions with just a few lines of code

# Simulate large frequency large_loss_frequency = simulate_values( "Poisson", parameters=mean_frequency, name="Large Loss Frequency", ) # Simulate individual large severity based on the simulated frequency large_losses = simulate_values( "Gamma", parameters={"target mean": 2000, "target std": 1000}, adjustment_parameters={"shift": 1000}, frequency=large_loss_frequency, name="Large Losses", )

Advantages of using CaPytal

CaPytal brings all your simulation functionality inside one convenient function

  • Generates a CaPytal Variable ready to use in downstream analysis
  • Simulate values for one or more element (class, class/year etc) in a single function call
  • Inputs match up by dimension and index and produces a properly indexed result Variable
  • Named Variables allow control of simulation error and audit
  • Automatic sense checking of simulated outputs
  • Specify parameters directly or in terms of moments or percentiles
  • Apply adjustments to distributions like shifts, truncations and caps
🔗

Correlation Modelling

Apply sophisticated dependency structures between risk classes and risk areas using copulas with managed dependency groups

Multiple copula types
Hierarchical structures supported
Tracks dependency groups internally

Apply copula based correlation structures easily

Simple functions for appling correlations between elements within a Variable or between corresponding elements from different Variables

# Apply correlation between attritional and large loss frequency by class apply_pairwise_correlation( variable1=large_loss_frequency, variable2=attritional_losses, copula_type="Gumbel", parameters=2, ) # Apply copula to total losses between classes apply_element_correlation( variable=aggregate_losses, copula_type="t", parameters=0.5, dof=7, )

Advantages of using CaPytal

CaPytal allows flexible copula based correlation modelling modelling using two simple functions

  • Allows a range of copula options, like Gaussan, Student's T, and Gumbel
  • Simple functions for imposing correlations between elements within a Variable or between Variables
  • Correlation inputs match up by dimension and index against Variables being acted on
  • Options to coerce input correlations into positive semi definite form or not
  • Automatic validation for convergene to target correlations
  • Checks for existing dependencies between Variables being correlated to avoid over specification
🛡️

Reinsurance Modelling

Model complex reinsurance structures with XoL, QS, inuring layers, deemed layers, complex programs simply

Interactive dashboards for understanding and editing structure
Wide range on prebuilt functionality
Easily extendable to custom program and contract types

Advantages of using CaPytal

Prebuilt components for modelling and analysing outwards RI, from simple contracts to complex structures with hundreds of programs

  • Allows fully data driven modelling from a database of programs/contracts and parameters
  • Allows for interactive setup of structures one contract at a time though notebooks with minimal code
  • Object orientated approach allows programs and contracts to be interacted with and reused within an overall structure
  • Interactive dashboad for inspecting structure and underlying programs and contracts, editing parameters and rerunning
  • Handles complex inuring relationships easily
  • Rich diagnostics and visualisations to help with understanding and validation of modelled stuctures
  • Easily extesible to custom program and contract types as subclasses of the core program and contract base classes

📊 Intuitive Data Handling

Work with actuarial data using familiar concepts - Variables, Programs, and Layers - without wrestling with raw dataframes.

🔧 Built on NumPy & Pandas

Leverage the proven performance and reliability of Python's scientific computing foundation.

📈 Rich Visualization

Generate publication-ready charts and reports with simple method calls integrated into your workflow.

🔬 Comprehensively Tested

Supported by a robust automated testing framework. Request to see our test suite to see exactly what the CaPytal package does in every situation.

"CaPytal is a fantastic package and it is clear that it is built by people with a lot of experience with capital modelling. It fits the workflow perfectly and the dashboards make it easy to use the model with business stakeholders."
— Lead Capital Actuary

Bespoke Development Services

Our team combines deep actuarial expertise with modern Python development to deliver custom solutions that fit your exact requirements. We don't just build software - we build solutions that understand your business.

Our Approach

🎯 Discovery & Design

We work closely with your team to understand your modeling requirements, regulatory constraints, and business objectives before writing a single line of code.

⚡ Rapid Prototyping

Using CaPytal as our foundation, we can quickly build and iterate on model prototypes to validate approaches and get early feedback.

🚀 Production Implementation

Full deployment with comprehensive documentation, testing, and knowledge transfer to ensure your team can maintain and extend the solution.

🛠️ Ongoing Support

Continued support for enhancements, regulatory changes, and performance optimization as your needs evolve.

What We Deliver

Current Capabilities

We're currently best positioned to deliver bespoke capital model development accelerated by the CaPytal package. This allows us to build sophisticated models much faster than traditional approaches while maintaining full transparency and customisation.

"Using CaPytal massively accelerates internal model development. It makes a lot of things very easy so we can focus on the methodology rather than the implementation."
— Head of Capital, Reinsurer

Roadmap & Future Solutions

We're building toward complete end-to-end actuarial technology solutions that integrate seamlessly with modern cloud infrastructure and business workflows.

Coming in 2025

📝 Data & Run Management

Version control and governance for model runs, data sets, and results. Track changes, compare versions, and ensure reproducibility.

📊 Interactive Dashboards

Real-time model monitoring, results visualization, and drill-down analytics accessible to both technical and business users.

📦 Off-the-Shelf Model Library

Complete end-to-end capital model implementations ready to deploy. Pre-built solutions covering common use cases with full documentation and regulatory reporting.

☁️ Cloud-Native Deployment

Scalable model execution on AWS/Azure with automatic scaling, cost optimization, and enterprise security.

Vision: Complete Platform

Our long-term vision is a complete actuarial technology platform that handles the entire modeling lifecycle:

Built for Modern Workflows

Unlike traditional actuarial software that forces you into rigid workflows, our platform adapts to how you actually work. Whether you prefer Jupyter notebooks, VS Code, or web interfaces, we meet you where you are.

Ready to Get Started?

Whether you're looking to explore CaPytal for your own projects or need a complete bespoke solution, we're here to help. Let's discuss how Python-powered actuarial technology can transform your modeling workflows.

Request Demo Discuss Your Project