Oficiais de Emprestimos Comerciais
Negócios e FinançasExposição à IA
- Fonte dos dados: BLSPublicado: 2026-08
Muito alto· relativa
BaixoQuatro faixas relativasMuito altoValor por grupo ocupacional
Escala, base e fonte
Quatro faixas relativas (Baixo / Moderado / Alto / Muito alto)
831 ocupações detalhadas da tabela de projeções de emprego do BLS. O valor é atribuído por código da National Employment Matrix (NEM), pelo que as ocupações que partilham um código NEM recebem a mesma banda
- Fonte dos dados: AnthropicPublicado: 2026-03
0.186
0.000Intervalo dos valores aqui apresentados0.745Escala, base e fonte
Índice de exposição observada, 0–1 tal como publicado
Mapeado sobre tarefas O*NET
- Fonte dos dados: ILOPublicado: 2025
0.60
0.09Intervalo dos valores aqui apresentados0.70Valor por grupo ocupacional
Escala, base e fonte
Índice de exposição à IA generativa, 0–1 tal como publicado
Grupo de base CITP-08 — todas as ocupações com o mesmo código recebem este valor
Calculado por este site, não publicado pela OIT: das 1.012 ocupações que este site liga ao conjunto de dados da OIT, 4% atingem ou superam este valor.
Que tipo de valor esta fonte publica
A categoria de BLS é uma posição relativa, não um nível absoluto, e também não é uma medição de primeira mão: agrupa em quatro faixas as posições percentis da ocupação em vários estudos publicados. Não é uma previsão de emprego ou de salários, não é uma probabilidade de adoção e não distingue automação de aumento.
Task-level exposure
Apenas tarefas expostas| Task | Claude.aiRaw / share % |
|---|---|
Explain to customers the different types of loans and credit options that are available, as well as the terms of those services.13-2072 | 0.052264.8 |
Work with clients to identify their financial goals and to find ways of reaching those goals.13-2072 | 0.013516.7 |
Market bank products to individuals and firms, promoting bank services that may meet customers' needs.13-2072 | 0.00799.8 |
Analyze potential loan markets and develop referral networks to locate prospects for loans.13-2072 | 0.00516.4 |
Confer with underwriters to aid in resolving mortgage application problems.13-2072 | 0.00182.3 |
| Not observed on any surface — 18 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | |
Approve loans within specified limits, and refer loan applications outside those limits to management for approval. | —0 |
Meet with applicants to obtain information for loan applications and to answer questions about the process. | —0 |
Analyze applicants' financial status, credit, and property evaluations to determine feasibility of granting loans. | —0 |
Obtain and compile copies of loan applicants' credit histories, corporate financial statements, and other financial information. | —0 |
Review and update credit and loan files. | —0 |
Review loan agreements to ensure that they are complete and accurate according to policy. | —0 |
Compute payment schedules. | —0 |
Stay abreast of new types of loans and other financial services and products to better meet customers' needs. | —0 |
Submit applications to credit analysts for verification and recommendation. | —0 |
Handle customer complaints and take appropriate action to resolve them. | —0 |
Negotiate payment arrangements with customers who have delinquent loans. | —0 |
Supervise loan personnel. | —0 |
Set credit policies, credit lines, procedures and standards in conjunction with senior managers. | —0 |
Provide special services such as investment banking for clients with more specialized needs. | —0 |
Prepare reports to send to customers whose accounts are delinquent, and forward irreconcilable accounts for collector action. | —0 |
Arrange for maintenance and liquidation of delinquent properties. | —0 |
Interview, hire, and train new employees. | —0 |
Petition courts to transfer titles and deeds of collateral to banks. | —0 |
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 | βE1 + 0.5 × E2 |
|---|---|
Explain to customers the different types of loans and credit options that are available, as well as the terms of those services.O*NET Task ID 3410 | 1.0 |
Review loan agreements to ensure that they are complete and accurate according to policy.O*NET Task ID 3413 | 1.0 |
Compute payment schedules.O*NET Task ID 3414 | 1.0 |
Prepare reports to send to customers whose accounts are delinquent, and forward irreconcilable accounts for collector action.O*NET Task ID 3426 | 1.0 |
Authorize or sign mail collection letters.O*NET Task ID 21636 | 1.0 |
Review billing for accuracy.O*NET Task ID 21647 | 1.0 |
Approve loans within specified limits, and refer loan applications outside those limits to management for approval.O*NET Task ID 3407 | 0.5 |
Meet with applicants to obtain information for loan applications and to answer questions about the process.O*NET Task ID 3408 | 0.5 |
Analyze applicants' financial status, credit, and property evaluations to determine feasibility of granting loans.O*NET Task ID 3409 | 0.5 |
Obtain and compile copies of loan applicants' credit histories, corporate financial statements, and other financial information.O*NET Task ID 3411 | 0.5 |
Supervise loan personnel.O*NET Task ID 3422 | 0.0 |
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