Business User Guide

Welcome to the Ergodic Insurance Optimization Business User Guide. This guide will help you use our advanced simulation framework to make data-driven decisions about insurance retentions and limit selections for your company.

This guide is designed for:

• CFOs and Financial Decision Makers who need to optimize insurance spending

• Risk Managers evaluating insurance program structures

• Entry-level Actuaries learning practical insurance optimization

• Business Owners seeking to balance growth and risk protection

No advanced mathematics or programming knowledge is required. We’ll walk you through everything step-by-step using practical examples and clear explanations.

Guide Contents:

• Executive Summary
  • The Insurance Optimization Paradox
  • The N=1 Problem
  • Time Average vs. Ensemble Average
  • The Bottom Line Impact
  • Real Numbers Example
  • Why Traditional Analysis Fails
  • The Ergodic Solution
  • Key Takeaways for Decision Makers
  • Your Next Steps
• Quick Start Guide
  • Prerequisites
  • Step 1: Understanding Your Company Profile
  • Step 2: Defining Your Risk Profile
  • Step 3: Exploring Insurance Structures
  • Step 4: Running Your First Simulation
  • Step 5: Using Pre-Built Notebooks
  • Step 6: Interpreting Initial Results
  • Quick Decision Rules
  • Next Steps
  • Common Issues
  • Ready for More?
• Running Your Analysis
  • Part 1: Setting Up Your Analysis Environment
  • Part 2: Defining Your Business Model
  • Part 3: Configuring Loss Distributions
  • Part 4: Running Simulations
  • Part 5: Analyzing Results
  • Part 6: Using Analysis Notebooks
  • Part 7: Generating Reports
  • Best Practices
  • Next Steps
• Decision Framework
  • The Three Critical Questions
  • Red Flags to Avoid
  • Implementation Checklist
  • Decision Rules by Company Type
  • Decision Metrics Dashboard
  • When to Review Your Decision
  • Key Takeaways
  • Next Steps
• Model Cases
  • Model Case 1: Widget Manufacturing Company
  • Model Case 2: High-Growth Technology Startup
  • Model Case 3: Stable Utility Company
  • Model Case 4: Comparison Across Industries
  • Implementation Lessons
  • TODO: Real-World Validation
  • Your Next Steps
• Advanced Topics
  • Customizing Loss Distributions
  • Correlation Modeling
  • Multi-Year Optimization
  • Advanced Stochastic Processes
  • Alternative Risk Transfer
  • Performance Optimization
  • Next Steps
• Hamilton-Jacobi-Bellman (HJB) Solver User Guide
  • Introduction
  • When to Use the HJB Solver
  • Mathematical Foundation
  • Core Components
  • Complete Example: Insurance Optimization
  • Advanced Topics
  • Performance Optimization
  • Troubleshooting Guide
  • Integration with Simulation Framework
  • Best Practices Summary
  • Conclusion
  • References
• Frequently Asked Questions
  • General Questions
  • Technical Questions
  • Implementation Questions
  • Common Pitfalls
  • Modeling Questions
  • Troubleshooting
  • Still Have Questions?
• Glossary
  • Insurance Terms
  • Mathematical Terms
  • Business Terms
  • Ergodic Framework Terms
  • Simulation Parameters
  • Industry-Specific Terms
  • Acronyms
  • Need More Definitions?

Getting Started

If you’re new to ergodic insurance optimization, we recommend reading the sections in order:

1. Start with the Executive Summary to understand the core concepts

2. Follow the Quick Start Guide to set up your first analysis

3. Use Running Your Analysis to perform your own company assessment

4. Apply the Decision Framework to make optimal choices

5. Review Model Cases for realistic examples

For Help

• Check the Frequently Asked Questions for common questions

• Consult the Glossary for term definitions

• Review example notebooks in ergodic_insurance/notebooks/

• Open an issue on GitHub

• Contact: Alex Filiakov (alexfiliakov@gmail.com)

Key Insight

The Insurance Paradox: Traditional insurance analysis uses ensemble averages (expected values across many companies). But your company experiences time averages (growth over years). These can differ dramatically. Our framework shows that paying 200-500% of expected losses can be optimal when viewed through the lens of time-average growth.

Ready to transform insurance from a cost center to a growth enabler? Let’s begin!