Loan Interviewers and Clerks
In short: today's best AI models could do about 72% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 28% of the time, stays with people.
Interview loan applicants to elicit information; investigate applicants' backgrounds and verify references; prepare loan request papers; and forward findings, reports, and documents to appraisal department. Review loan papers to ensure completeness, and complete transactions between loan establishment, borrowers, and sellers upon approval of loan.
164,790 people do this job in the US. $50,020 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work29 h
- Desk work AI can't do yet0 h
- Stays with people11 h
Loan Interviewers and Clerks, now: of a 40-hour week, AI could take on 0 hours, 29 hours become checking its work, 0 hours are desk work it can't do yet, and 11 hours stay with people.
The largest pieces: Verify application and closing documents (about 4 h, a person checks); Calculate and correct loan figures (about 3 h, a person checks); Prepare loan documents (about 3 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 37%
- 35%
- 8%
- 20%
- 0%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 72% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 3%. With Claude Mythos Preview (early), measured in April 2026, 71%. Today's estimate: 72%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 18 tasks showed up. Within each of Anthropic's methods, never across a change: 0.032% to 0.024% (released February and March 2025); 0.0072% to 0.014% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.032% | 352 of 708 | 4 of 18 |
| Released March 2025 | 0.024% | 391 of 703 | 3 of 18 |
| The week of Aug 4, 2025 (released September 2025) | 0.0072% | 495 of 655 | 2 of 18 |
| The week of Nov 13, 2025 (released January 2026) | 0.013% | 439 of 672 | 4 of 18 |
| The week of Feb 5, 2026 (released March 2026) | 0.014% | 450 of 677 | 4 of 18 |
| April 2026 (released June 2026) | none | n/a | 0 of 18 |
| May 2026 (released June 2026) | none | n/a | 0 of 18 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates almost none of this job's working time as physical work, so robots do not reach it.
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
28% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Interview loan applicants, the in-person work, 9%
- Schedule and conduct closings, the in-person work, 6%
- Answer questions about loans, the conversation, 5%
- Present repayment schedules, the in-person work, 4%
- Check credit and references, the conversation, 3%
- Tell customers the decision, the conversation, 1%
What becomes checking the machine
72% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it.
- Verify application and closing documents, costly if wrong, 9%
- Calculate and correct loan figures, costly if wrong, 8%
- Prepare loan documents, costly if wrong, 7%
- Check collateral value, costly if wrong, 7%
- Record loan applications and disbursements, costly if wrong, 7%
- Assemble closing documents, costly if wrong, 6%
What to learn
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Handling protected records. Much of the work touches protected personal records: knowing what may be shared with a model, and how, is part of the job.
- Briefing a model and checking its drafts. About 37% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- Running AI inside the business systems. About 35% of the time is work inside business systems, which a model can do only once it is connected: knowing the systems well enough to set that up and watch it.
- The conversations. About 28% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 18 tasks from .
| Task | ||||
|---|---|---|---|---|
| Interview loan applicants to obtain personal and financial data and to assist in completing applications.Asking the applicant at the desk and entering the answers.Done daily by most who do it. AI observed on this task. | 13% | 38 min17 min to 1.3 h | In person 70%, systems 30% | 30%Desk part half by now |
| Verify and examine information and accuracy of loan application and closing documents.Reading the documents for accuracy.Done daily by most who do it. | 9% | 33 min17 min to 1.3 h | Documents 100% | 100%Half by now |
| Calculate, review, and correct errors on interest, principal, payment, and closing costs, using computers or calculators.Checking interest, principal and closing costs and correcting errors.Done daily by most who do it. | 8% | 21 min8 min to 50 min | Documents 60%, systems 40% | 100%Half by now |
| Schedule and conduct closings of mortgage transactions.Closings held in person, with the scheduling.Done more than monthly by most who do it. | 8% | 1.3 h38 min to 2.5 h | In person 70%, systems 30% | 30%Desk part half by now |
| Prepare and type loan applications, closing documents, legal documents, letters, forms, government notices, and checks, using computers.Applications, closing documents and letters prepared on the computer.Done daily by most who do it. | 7% | 38 min17 min to 1.3 h | Documents 50%, systems 50% | 100%Half by now |
| Check value of customer collateral to be held as loan security.Reading the valuation of the security offered.Done daily by most who do it. | 7% | 25 min13 min to 1.1 h | Documents 100% | 100%Half by now |
| Record applications for loan and credit, loan information, and disbursements of funds, using computers.Entries in the loan system.Done daily by most who do it. | 7% | 17 min8 min to 38 min | Systems 100% | 100%Half by now |
| Assemble and compile documents for loan closings, such as title abstracts, insurance forms, loan forms, and tax receipts.Compiling abstracts, forms and receipts for the closing.Done daily by most who do it. AI observed on this task. | 6% | 42 min25 min to 1.3 h | Documents 70%, systems 30% | 100%Half by now |
| Submit loan applications with recommendation for underwriting approval.Writing the recommendation and submitting the file.Done daily by most who do it. | 6% | 25 min13 min to 50 min | Documents 60%, systems 40% | 100%Half by now |
| Contact credit bureaus, employers, and other sources to check applicants' credit and personal references.Bureau pulls in the system and calls to employers and references.Done daily by most who do it. | 6% | 25 min13 min to 1.3 h | Systems 50%, conversation 50% | 50%Desk part half by now |
| Answer questions and advise customers regarding loans and transactions.Questions from customers at the desk and by phone.Done daily by most who do it. | 5% | 13 min4 min to 25 min | Conversation 50%, in person 50% | Stays with people |
| Review customer accounts to determine whether payments are made on time and that other loan terms are being followed.Reading accounts in the system for late payments and broken terms.Done more than weekly by most who do it. | 4% | 21 min8 min to 38 min | Systems 60%, documents 40% | 100%Half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Loan Interviewers and Clerks is within reach of AI now?
- An estimated 72% of the working time is within reach of AI models now and 72% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Loan Interviewers and Clerks come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Verify application and closing documents (100% of the task's time now); Calculate and correct loan figures (100% of the task's time now); and Prepare loan documents (100% of the task's time now).
- Which tasks of Loan Interviewers and Clerks stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Answer questions about loans; and Present repayment schedules. Together such tasks are about 9% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Loan Interviewers and Clerks learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are reviewing work you did not do yourself; handling protected records; and briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 28% of the working time stays with people, 72% becomes checking a model's work and 0% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Loan Interviewers and Clerks?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 20%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Loan Interviewers and Clerks?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 18 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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