# Chain Ladder

> Use this tool when you need to perform loss reserving calculations and analyze insurance loss data. It solves problems related to estimating future claims and uncertainty ranges, providing outputs such as IBNR projections and ultimate loss estimates from insurance loss data inputs. The Chain Ladder method is particularly useful in contexts where actuaries and insurance professionals require reliable loss reserving calculations and data analysis.

Canonical page: https://skillsregistry.net/skills/datalattice-chain-ladder  
JSON: https://api.skillsregistry.net/v1/skills/datalattice-chain-ladder

## Description

Chain Ladder provides actuaries and insurance professionals with MCP tools for loss reserving calculations using the chain-ladder method. It computes IBNR projections, ultimate loss estimates, Mack stochastic uncertainty ranges, assumption diagnostics, and triangle transformations for insurance loss data analysis.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/datalattice-chain-ladder)
- **Repository:** <https://github.com/datalattice/mcp-chainladder>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "datalattice-chain-ladder"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/datalattice-chain-ladder` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/datalattice-chain-ladder/pull`

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