Pith Number

pith:MELTFVWT

pith:2025:MELTFVWTLHNQN3Y3DYMXNXTV42

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Advanced Applications of Generative AI in Actuarial Science: Case Studies Beyond ChatGPT

Iris Nonneman, Simon Hatzesberger

Generative AI supports actuarial practice through four concrete case studies in insurance.

arxiv:2506.18942 v3 · 2025-06-22 · cs.CY · q-fin.RM

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\usepackage{pith}
\pithnumber{MELTFVWTLHNQN3Y3DYMXNXTV42}

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Record completeness

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Generative AI can support actuarial practice through four implemented case studies: LLMs for extracting features from text in claim cost prediction, RAG for structuring information from annual reports, vision-enabled LLMs for car damage classification, and a multi-agent system for migrating legacy R code to Python.

C2weakest assumption

The described implementations function reliably enough for practical use in regulated insurance environments despite the challenges of reproducibility, privacy, and governance that the paper itself lists in its final section.

C3one line summary

Four implemented case studies demonstrate generative AI supporting actuarial tasks in claim cost prediction, market report analysis, image-based damage assessment, and legacy code migration.

Formal links

2 machine-checked theorem links

Cited by

1 paper in Pith

Agentic AI and Retrieval-Augmented Models in Straight-Through Underwriting

Receipt and verification

First computed	2026-06-26T00:15:22.215889Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

611732d6d359db06ef1b1e1976de75e685a937d59aa551d09846ffe9a86feda2

Aliases

arxiv: 2506.18942 · arxiv_version: 2506.18942v3 · doi: 10.48550/arxiv.2506.18942 · pith_short_12: MELTFVWTLHNQ · pith_short_16: MELTFVWTLHNQN3Y3 · pith_short_8: MELTFVWT

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/MELTFVWTLHNQN3Y3DYMXNXTV42 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 611732d6d359db06ef1b1e1976de75e685a937d59aa551d09846ffe9a86feda2

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "19db42fbec2129ce6ab960014b8f44f8798c5003ad995369c62eec378f9fd490",
    "cross_cats_sorted": [
      "q-fin.RM"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CY",
    "submitted_at": "2025-06-22T19:36:03Z",
    "title_canon_sha256": "017d27c5e2706a5ce1df8b160ba9b1571e6596d5fcf0acb347a3e674c06f649e"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2506.18942",
    "kind": "arxiv",
    "version": 3
  }
}