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reserving-methods

Apply Chain Ladder and Bornhuetter-Ferguson methods to estimate ultimate loss reserves.

9|2|Updated Feb 10, 2026
Search Tags:#data analysis#actuarial#reserving#chain ladder#loss development#ultimate projection
One-click install
npx skills add https://github.com/cas-team-analyst/claude-code --skill reserving-methods
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reserving-methods
Source: https://github.com/cas-team-analyst/claude-code/tree/main/.claude/skills/reserving-methods
Command: npx skills add https://github.com/cas-team-analyst/claude-code --skill reserving-methods

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, openpyxl, pathlib, json, re, shutil, and includes scripts (resource) and assets (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex process of actuarial reserve estimation, providing actuaries with robust tools to select and apply various reserving methods.

Core Features & Use Cases

  • Chain Ladder Method: Implements the widely used Chain Ladder technique for projecting ultimate losses.
  • Bornhuetter-Ferguson Method: Includes a framework for the BF method (under construction).
  • Data Preparation & Enhancement: Scripts to clean, format, and enrich raw actuarial data.
  • Diagnostic Analysis: Generates key actuarial metrics to support informed LDF selection.
  • Automated Selections: Provides initial LDF selections based on data analysis, with options for user overrides.
  • Ultimate Projection: Calculates projected ultimate losses under different scenarios.
  • Reporting: Generates interactive HTML reports for data visualization and analysis.

Quick Start

Use the reserving-methods skill to apply the chain-ladder method to your actuarial data.

Frequently Asked Questions about reserving-methods

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate loss development factors and project ultimate losses using the chain ladder method?▼

To calculate loss development factors and project ultimate losses, this Skill applies the chain ladder method to your actuarial data, automating LDF calculation, diagnostic analysis, and ultimate loss projection with interactive HTML reporting.

What is the best way to automate LDF selection for actuarial reserving?▼

The best way to automate LDF selection for actuarial reserving is to use this Skill's automated selection feature, which generates initial loss development factor selections based on data analysis, while also supporting user-defined overrides for selection refinement.

Can I use pandas and numpy to prepare raw actuarial data for loss development projections?▼

Yes, you can use this Skill to prepare raw actuarial data for loss development projections, as it leverages pandas and numpy to run scripts that clean, format, and enrich your data prior to applying reserving methods.

Does the Bornhuetter-Ferguson method work with chain ladder ultimate loss projections?▼

The Bornhuetter-Ferguson method is included as a framework for ultimate loss projection alongside the chain ladder method, but the BF method component is currently under construction and not yet fully implemented.

How do I generate interactive HTML reports for actuarial reserve estimation?▼

To generate interactive HTML reports for actuarial reserve estimation, this Skill processes your prepared data through the chain ladder projection workflow and outputs visual HTML reports for diagnostic analysis and ultimate loss review.

What are the limitations of using automated LDF selections for ultimate loss reserves?▼

A limitation of automated LDF selections is that they provide initial estimates based solely on data analysis, meaning actuaries must still apply manual user-defined overrides to refine selections and ensure accurate ultimate loss reserves.

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