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Run chain-ladder reserving, IBNR estimates, and actuarial diagnostics in natural language.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-chainladder" yet — see the docs or source repo.
Using this cumulative claims triangle, run a chain-ladder analysis and return ultimate losses, reported losses, and IBNR by accident year, plus the key assumptions.
A year-by-year reserving table with ultimate losses, IBNR, and a brief methodology summary.
Apply the Mack chain-ladder method to this claims triangle and estimate the standard error, coefficient of variation, and confidence intervals for each accident year and in total.
Uncertainty metrics and interval estimates to assess reserving variability.
Run diagnostic tests on this loss development triangle, identify unusual development periods, possible structural changes, and whether chain-ladder is appropriate to use directly.
A diagnostic assessment with anomaly notes and recommendations on whether model adjustments are needed.
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Perform accurate arithmetic, trigonometric, logarithmic, and other math calculations.
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Analyze industrial chains with enterprise search, patents, bidding, and supply data.