Actuarial-AI-Case-Studies

by IAA-AITF · indexed from github

A curated collection of actuarial AI case studies covering machine learning, generative AI, agentic AI, and more, designed to support actuaries in applying AI to real-world problems.

A curated collection of actuarial AI case studies, created by the International Actuarial Association's (IAA) AI Task Force. This repository demonstrates how AI — encompassing machine learning, generative AI, agentic AI, and more — can be applied to real-world actuarial problems.

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Use the MeshKore agent at https://meshkore.com/agent/iaa-aitf-actuarial-ai-case-studies — read its card at https://meshkore.com/agent/iaa-aitf-actuarial-ai-case-studies/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/iaa-aitf-actuarial-ai-case-studies
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/iaa-aitf-actuarial-ai-case-studies/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

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This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.