# Insurance Underwriters

> Review individual applications for insurance to evaluate degree of risk involved and determine acceptance of applications.

- **SOC code:** 13-2053.00
- **Canonical URL:** https://singulariki.com/roles/role-13-2053-00
- **Also known as:** Account Underwriter, Life Underwriter, Personal Lines Underwriter, Underwriter, Automobile and Property Underwriter, Commercial Lines Underwriter, Health Underwriter, Underwriting Consultant
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property.
- Decline excessive risks.
- Write to field representatives, medical personnel, or others to obtain further information, quote rates, or explain company underwriting policies.
- Evaluate possibility of losses due to catastrophe or excessive insurance.
- Review company records to determine amount of insurance in force on single risk or group of closely related risks.
- Decrease value of policy when risk is substandard and specify applicable endorsements or apply rating to ensure safe, profitable distribution of risks, using reference materials.
- Authorize reinsurance of policy when risk is high.

**Emerging tasks** (O*NET):
- Answer agents' questions about insurance coverage.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- English Language _(knowledge)_
- Customer and Personal Service _(knowledge)_
- Written Comprehension _(ability)_
- Reading Comprehension _(essential_skill)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Written Expression _(ability)_
- Inductive Reasoning _(ability)_
- Speaking _(essential_skill)_
- Oral Expression _(ability)_
- Judgment and Decision Making _(transferable_skill)_

**Skills in demand:**
- English Language _(Common Skill)_
- Writing _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Mathematics _(Common Skill)_
- Speech Recognition _(Specialized Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- C++ _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_
- Anodas Software Limited Phoenix
- Consilience Software Maven Insurance Automation Suite
- CSC nbAccelerator
- Database software

## AI exposure & outlook

- **AI task-overlap index:** 83rd percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 89th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 95th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 55th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 99th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -2.6% growth (Declining); 8.2k annual openings; 127k → 123.7k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $79,880; 107,820 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 45% automation, — augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** none.

**Tasks most handed to AI here:**
- Decline excessive risks. _(1.2% of measured AI use; none)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me decline excessive risks.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

---
_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-13-2053-00_