Insurance Underwriters
Business and Financial Operations Occupations- O*NET-SOC code
- 13-2053.00
Review individual applications for insurance to evaluate degree of risk involved and determine acceptance of applications.
- Data source: BLSPublished: 2026-08
Very high· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.063
0.000Range of values carried here0.745Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
- Data source: ILOPublished: 2025
0.53
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Show 4 hidden tasks7 rated tasks · 7 tasks with β ≥ 0.5 (100.0%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- All rated tasks are in the O*NET 31.0 task list.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
| Task (O*NET 20.1) | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Decline excessive risks.13-2053.00 | 0.003550.7 | 0.002865.1 |
Write to field representatives, medical personnel, and others to obtain further information, quote rates, or explain company underwriting policies.13-2053.00 | 0.001927.5 | —0 |
Examine documents to determine degree of risk from such factors as applicant financial standing and value and condition of property.13-2053.00 | 0.001521.7 | 0.001534.9 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task (O*NET 27.2) | βE1 + 0.5 × E2 |
|---|---|
Write to field representatives, medical personnel, or others to obtain further information, quote rates, or explain company underwriting policies.O*NET Task ID 1262 | 1.0 |
Decline excessive risks.O*NET Task ID 1261 | 0.5 |
Evaluate possibility of losses due to catastrophe or excessive insurance.O*NET Task ID 1263 | 0.5 |
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.O*NET Task ID 1264 | 0.5 |
Review company records to determine amount of insurance in force on single risk or group of closely related risks.O*NET Task ID 1265 | 0.5 |
Authorize reinsurance of policy when risk is high.O*NET Task ID 1266 | 0.5 |
Examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property.O*NET Task ID 21045 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
All O*NET 31.0 task statements (7)
All O*NET 31.0 task statements for this occupation (English, as published; task type core or supplemental). Exposure values are not listed here; they are in the table above, next to each task statement as worded in the O*NET version each source used.
| Task (O*NET 31.0) | Type |
|---|---|
| Decline excessive risks. | Core |
| Write to field representatives, medical personnel, or others to obtain further information, quote rates, or explain company underwriting policies. | Core |
| Evaluate possibility of losses due to catastrophe or excessive insurance. | Core |
| 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. | Core |
| Review company records to determine amount of insurance in force on single risk or group of closely related risks. | Core |
| Authorize reinsurance of policy when risk is high. | Core |
| Examine documents to determine degree of risk from factors such as applicant health, financial standing and value, and condition of property. | Core |
0.00/ 3· Robot exposure index
Scale, basis and source
Each physical task is graded 0–3 by the setting in which robots that have been deployed, sold or demonstrated could do it (0 none · 1 purpose-built robot settings such as a fenced machine cell or a bottling line · 2 structured facilities such as a hospital pharmacy or a container port · 3 unstructured settings such as a private home or a construction site), and the grades are averaged by share of working time
Physical tasks among this occupation's O*NET 29.3 tasks
Anthropic estimated the grades and time shares with Claude Opus 5 using web search, as of 2026.
The robot exposure index is a different measure from the AI exposure figures on this site and cannot be added to or compared with them. It does not measure actual adoption or cost, and 0 also covers occupations with no physical tasks.
Tier of each physical task
None of this occupation's O*NET 29.3 tasks is classified as a physical task.
Occupation information
Employment outlook (BLS)
- Employment, 2025
- 126K
- Projected employment, 2035
- 121K
- Change (2025–35)
- -3.8%
- Median annual wage, 2025
- $81,370
- Typical education needed for entry
- Bachelor's degree
Korea classification links (KSCO)
Links from the current release of the Korea Occupation Direct Crosswalk v1.1, made by AI Changing Work. Relation values are read from the O*NET-SOC occupation side.
| KSCO code | KSCO title | Relation | Status |
|---|---|---|---|
| 28292 | 보험 인수 심사원 | Same scope | confirmed |
Relation and status definitions(kr-direct v1.1)
ILO occupational description
AI Changing Work links the ISCO-08 unit groups below to this occupation by applying the U.S. Bureau of Labor Statistics crosswalks (2018 SOC to 2010 SOC, 2010 SOC to ISCO-08) as published, without case-by-case selection; each link may be whole or partial.
- ISCO-08 3321Insurance Representatives
The definition, tasks and examples below are the ILO's description of that unit group, not of this occupation.
Insurance representatives advise on and sell life, accident, automobile, liability, endowment, fire, marine and other types of insurance to new and established clients.
Tasks
- (a) obtaining information about customers’ circumstances necessary to determine appropriate type of insurance and conditions;
- (b) negotiating with customers to determine type and degree of risk for which insurance is required;
- (c) explaining details of insurance and conditions, risk coverage premiums and benefits to customers;
- (d) assisting clients to determine the type and level of coverage required, calculating premiums and establishing method of payment;
- (e) negotiating and placing reinsurance contracts;
- (f) advising on, negotiating terms for and placing insurance contracts for large or special types of projects, installations or risks.
Example occupations
Insurance agent · Insurance broker · Insurance underwriter
Sources: ILO ISCO-08 — details: Credits
ESCO occupational vocabulary
Each entry below is matched to this occupation in the published ESCO-O*NET Crosswalk (version 1, 2022). The match types are that crosswalk's; the wording is AI Changing Work's.
- insurance underwriterESCO 3321.3Same scope
Insurance underwriters assess business risks and liability policies and make decisions about commercial property. They inspect the conditions of businesses’ properties, analyse inspection policies, assist with real estate and rent issues, prepare loan contracts and handle commercial risks in order to align them with business practices. Insurance underwriters analyse various information from prospective customers in order to assess the likelihood that they will report a claim. They work to minimise risk for the insurance company and make sure that the insurance premium aligns with the associated risks. They can be specialists in life insurance, health insurance, reinsurance, commercial insurance, mortgage insurance.
- property insurance underwriterESCO 3321.3.1This occupation is broader
Property insurance underwriters assess and determine the risk and coverage of a client's property insurance. They analyse and review underwriting policies according to legal regulations.
- insurance brokerESCO 3321.1Overlapping, not the same
Insurance brokers promote, sell and provide advice on various insurance policies such as life insurance, health insurance, accident insurance and fire insurance to individuals and organisations. They also work as intermediaries between individuals or organisations and insurance companies, and negotiate the best insurance policies for their clients, arranging insurance cover where needed. Insurance brokers engage with new prospective clients, provide them with quotes for their policy needs, assist them in the signing of new insurance contracts and propose specific solutions to their specific problems.
- mortgage loan underwriterESCO 3312.6Overlapping, not the same
Mortgage loan underwriters ensure compliance with underwriter guidelines. They participate in the implementation of new underwriting guidelines. They also review closed and denied loans.
Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
License: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
France classification links (ROME)
AI Changing Work's links between this occupation and ROME 4.0 job profiles, judged with AI models. Relations are read from this occupation's side. Links marked “provisional” were adopted on the judgments of two judges from the same model family (Claude) alone, or by an operator rule applied to their judgments, so they rest on weaker evidence than confirmed links.
| ROME code | ROME title (French) | Relation |
|---|---|---|
| C1110 | Souscripteur / Souscriptrice en assurances | Same scope |
| C1114 | Assureur / Assureuse maritime | This occupation is broader |
| C1121 | Inspecteur / Inspectrice des assurances | Related, not a match |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
Spain classification links (CNO-11)
AI Changing Work's links between this occupation and CNO-11 occupations, judged with AI models. Relations are read from this occupation's side.
| CNO-11 code | CNO-11 title (Spanish) | Relation |
|---|---|---|
| 3521 | Mediadores y agentes de seguros | Related, not a match |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
Germany classification links (KldB)
AI Changing Work's links between this occupation and KldB occupations, judged with AI models. Relations are read from this occupation's side.
| KldB code | KldB title (German) | Relation |
|---|---|---|
| 72133 | Versicherungskaufleute - komplexe Spezialistentätigkeiten | This occupation is narrower |
| 72132 | Versicherungskaufleute - fachlich ausgerichtete Tätigkeiten | Related, not a match |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
Japan classification links (JSCO)
AI Changing Work's links between this occupation and JSCO occupations, judged with AI models. Relations are read from this occupation's side.
| JSCO code | JSCO title (Japanese) | Relation |
|---|---|---|
| 184 | 金融・保険専門職業従事者 | Related, not a match |
| 259 | その他の一般事務従事者 | Related, not a match |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
Sources, licenses and AI Changing Work's modification and translation notices for this page: Credits & sources