Occupation · SOC 13-2071.00
Advise and educate individuals or organizations on acquiring and managing debt. May provide guidance in determining the best type of loan and explain loan requirements or restrictions. May help develop debt management plans or student financial aid packages. May advise on credit issues, or provide budget, mortgage, bankruptcy, or student financial aid counseling.
Also called: Certified Consumer Credit and Housing Counselor · Certified Credit Counselor · Credit Counselor · Housing Counselor · Accredited Financial Counselor · Certified Credit Consultant · Certified Credit and Housing Counselor · Financial Health Counselor · Personal Finance Counselor · Branch Credit Counselor · Consumer Credit Counselor · Consumer Lending Manager
Job family: Business and Financial Operations Occupations
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-13-2071-00/context.md directly.
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Independent published positions, read together — not a forecast.
95th-percentile task overlap — yet about 2,200 openings a year (+3.3% projected, BLS), and observed AI use leans 7158% copilot, not hand-off (AEI) . What exposure means →
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) High | 95th | 1.4 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 90th | 1.0 | |
| AI assistant applicability (Microsoft) High | 86th | 0.3 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.3), with simple added tooling (β 0.6), and including AI-powered software (γ 1.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.0 · 22nd percentile among occupations · Low
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Explain general financial topics to clients, such as credit report ratings, bankruptcy laws, consumer protection laws, wage attachments, or collection actions. | 16.1% | |
| Recommend strategies for clients to meet their financial goals, such as borrowing money through loans or loan programs, declaring bankruptcy, making budget adjustments, or enrolling in debt management plans. | 9.7% | |
| Prepare written documents to establish contracts with or communicate financial recommendations to clients. | 5.1% | |
| Create debt management plans, spending plans, or budgets to assist clients to meet financial goals. | 2.7% | |
| Review changes to financial, family, or employment situations to determine whether changes to existing debt management plans, spending plans, or budgets are needed. | 0.4% |
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +3.3% by 2034 |
| Projected annual openings | 2,200 |
| Employment 2024 → 2034 | 31,800 → 32,900 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Credit and Loans Officers · 3312 | 61% | Gradient 4 |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 71.6% working with AI · 24.4% handed to AI |
| Most common way people use AI here | Learning · you ask AI to explain or teach |
| Typical AI autonomy | 3.0 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 10.4% |
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Recommend strategies for clients to meet their financial goals, such as borrowing money through loans or loan programs, declaring bankruptcy, making budget adjustments, or enrolling in debt management plans. | Iteration | 7.7% |
| Explain general financial topics to clients, such as credit report ratings, bankruptcy laws, consumer protection laws, wage attachments, or collection actions. | Learning | 7.5% |
| Create debt management plans, spending plans, or budgets to assist clients to meet financial goals. | Iteration | 5.4% |
| Recommend educational materials or resources to clients on matters such as financial planning, budgeting, or credit. | Learning | 2.8% |
| Teach courses or seminars on topics such as budgeting, managing personal finances, or financial literacy. | Directive | 2.0% |
| Explain services or policies to clients, such as debt management program rules, the advantages and disadvantages of using services, or creditor concession policies. | Learning | 1.9% |
| Estimate time for debt repayment given amount of debt, interest rates, and available funds. | Directive | 0.9% |
| Prepare written documents to establish contracts with or communicate financial recommendations to clients. | Iteration | 0.7% |
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Explain services or policies to clients, such as debt management program rules, the advantages and disadvantages of using services, or creditor concession policies. | 99.5% | |
| Explain general financial topics to clients, such as credit report ratings, bankruptcy laws, consumer protection laws, wage attachments, or collection actions. | 99.3% | |
| Recommend educational materials or resources to clients on matters such as financial planning, budgeting, or credit. | 98.9% | |
| Review changes to financial, family, or employment situations to determine whether changes to existing debt management plans, spending plans, or budgets are needed. | 98.4% | |
| Prepare written documents to establish contracts with or communicate financial recommendations to clients. | 97.2% | |
| Estimate time for debt repayment given amount of debt, interest rates, and available funds. | 95.6% |
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
Help me recommend strategies for clients to meet their financial goals, such as borrowing money through loans or loan programs, declaring bankruptcy, making budget adjustments, or enrolling in debt management plans. From: Recommend strategies for clients to meet their financial goals, such as borrowing money through loans or loan programs, declaring bankruptcy, making budget adjustments, or enrolling in debt management plans. · 7.7% of measured AI use · task iteration
Help me explain general financial topics to clients, such as credit report ratings, bankruptcy laws, consumer protection laws, wage attachments, or collection actions. From: Explain general financial topics to clients, such as credit report ratings, bankruptcy laws, consumer protection laws, wage attachments, or collection actions. · 7.5% of measured AI use · learning
Help me create debt management plans, spending plans, or budgets to assist clients to meet financial goals. From: Create debt management plans, spending plans, or budgets to assist clients to meet financial goals. · 5.4% of measured AI use · task iteration
Help me recommend educational materials or resources to clients on matters such as financial planning, budgeting, or credit. From: Recommend educational materials or resources to clients on matters such as financial planning, budgeting, or credit. · 2.8% of measured AI use · learning
All 23 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
O*NET importance rating, from 1 (not important) to 5 (extremely important).
| Customer and Personal Service | 4.6 | |
| English Language | 4.1 | |
| Mathematics | 3.6 | |
| Administrative | 3.5 | |
| Education and Training | 3.4 | |
| Economics and Accounting | 3.3 | |
| Psychology | 3.0 |
| Oral Expression | 4.1 | |
| Oral Comprehension | 4.0 | |
| Written Comprehension | 3.9 | |
| Written Expression | 3.8 | |
| Problem Sensitivity | 3.8 | |
| Deductive Reasoning | 3.8 | |
| Inductive Reasoning | 3.8 | |
| Information Ordering | 3.3 | |
| Near Vision | 3.3 | |
| Speech Recognition | 3.3 | |
| Speech Clarity | 3.3 | |
| Fluency of Ideas | 3.1 | |
| Mathematical Reasoning | 3.1 | |
| Number Facility | 3.1 | |
| Selective Attention | 3.0 |
| Speaking | 4.0 | |
| Reading Comprehension | 3.9 | |
| Active Listening | 3.9 | |
| Writing | 3.8 | |
| Critical Thinking | 3.8 | |
| Active Learning | 3.6 | |
| Mathematics | 3.1 | |
| Learning Strategies | 3.1 | |
| Monitoring | 3.0 |
| Service Orientation | 3.6 | |
| Complex Problem Solving | 3.5 | |
| Judgment and Decision Making | 3.5 | |
| Persuasion | 3.4 | |
| Negotiation | 3.3 | |
| Social Perceptiveness | 3.1 | |
| Coordination | 3.1 | |
| Time Management | 3.1 | |
| Systems Evaluation | 3.0 |
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 41.
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
What to study: Business, Management, Marketing, and Related Support Services . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Share of people in this occupation at each level of education.
| Bachelor's Degree | 40.0% | |
| High School Diploma | 36.0% | |
| Post-Secondary Certificate | 12.0% | |
| Some College Courses | 8.0% | |
| Associate's Degree (or other 2-year degree) | 4.0% |
The interests and personal qualities O*NET associates with people who do this work.
| Dependability | 9.0 | |
| Attention to Detail | 8.0 | |
| Integrity | 7.0 | |
| Cautiousness | 6.0 | |
| Cooperation | 5.0 | |
| Social Orientation | 4.0 |
| Professional Advising | 5.9 | |
| Accounting | 5.0 | |
| Office Work | 5.0 | |
| Finance | 4.5 | |
| Social Service | 4.3 | |
| Personal Service | 3.8 | |
| Teaching/Education | 3.4 |
| Conventional | 5.3 | |
| Social | 4.9 | |
| Enterprising | 4.7 |
U.S. · annual wages (BLS OEWS)
| 10th percentile | $38,980 |
| 25th percentile | $45,420 |
| Median (50th) | $50,480 |
| 75th percentile | $61,760 |
| 90th percentile | $77,920 |
| People employed | 28,110 |
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Educational Services · Sector | 13,970 | $51,860 |
| Health Care and Social Assistance · Sector | 3,930 | $50,370 |
| Finance and Insurance · Sector | 3,920 | $49,580 |
| Professional, Scientific, and Technical Services · Sector | 3,480 | $48,380 |
| Management of Companies and Enterprises · Sector | 1,330 | $57,700 |
| Other Services (except Public Administration) · Sector | 640 | $44,500 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 310 | $43,560 |
| Retail Trade · Sector | 250 | $60,000 |
| Construction · Sector | 50 | $50,440 |
| Information · Sector | 30 | $46,860 |
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Educational Services · Sector | 5.62× | 13,970 |
| Finance and Insurance · Sector | 3.45× | 3,920 |
| Management of Companies and Enterprises · Sector | 2.6× | 1,330 |
| Professional, Scientific, and Technical Services · Sector | 1.77× | 3,480 |
| Health Care and Social Assistance · Sector | 0.93× | 3,930 |
| Other Services (except Public Administration) · Sector | 0.79× | 640 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 0.19× | 310 |
| Retail Trade · Sector | 0.09× | 250 |
Part of the Financial Services career cluster.
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
Options the data surfaces for Credit Counselors — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Capabilities this work builds that are used across many other occupations.
Occupations O*NET rates as related — the nearby moves on the map.
How people typically prepare for this work.
On the global GenAI exposure gradient this work sits around the 98th percentile of 427 international occupations.
Credit Counselors show 95th-percentile AI task overlap — and about 2,200 annual U.S. openings
Credit Counselors show 95th-percentile AI task overlap — and about 2,200 annual U.S. openings • Credit Counselors rank in the 95th percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 2,200 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+3.3%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $50,480, across about 28,110 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 72% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Credit Counselors". https://singulariki.com/roles/role-13-2071-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
Data compiled June 2, 2026. Figures are estimates, not advice.
Singulariki. "Credit Counselors." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-13-2071-00
Singulariki. (2026). Credit Counselors. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-13-2071-00
@misc{singulariki-role-13-2071-00,
title = {Credit Counselors},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-13-2071-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.