Last Update: 3/13/2026
Your role’s AI Resilience Score is
Median Score
Changing Fast
Evolving
Stable
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
What does this resilience result mean?
These roles are undergoing rapid transformation. Entry-level tasks may be automated, and career paths may look different in the near future.
AI Resilience Report for
They help people apply for loans by collecting financial information, reviewing documents, and making sure everything is correct and complete.
This role is changing fast
The career of Loan Interviewers and Clerks is labeled as "Changing fast" because AI is automating many routine tasks like data entry and form-filling, making those parts of the job quicker and more efficient. However, there's still a strong need for human skills like empathy, communication, and decision-making, as these roles involve interviewing applicants and answering their questions.
Read full analysisLearn more about how you can thrive in your career
Learn more about how you can thrive in your career
This role is changing fast
The career of Loan Interviewers and Clerks is labeled as "Changing fast" because AI is automating many routine tasks like data entry and form-filling, making those parts of the job quicker and more efficient. However, there's still a strong need for human skills like empathy, communication, and decision-making, as these roles involve interviewing applicants and answering their questions.
Read full analysisContributing Sources
We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.
AI Resilience
AI Resilience Model v1.0
AI Task Resilience
CareerVillage's proprietary model that estimates how resilient each occupation's tasks are to AI automation and augmentation
Microsoft's Working with AI
AI Applicability
Measures how applicable AI tools (like Bing Copilot) are to each occupation based on real usage patterns
Anthropic's Observed Exposure
AI Resilience
Based on observed patterns of how Claude is being used across occupational tasks in real conversations
Will Robots Take My Job
Automation Resilience
Estimates the probability of automation for each occupation based on research from Oxford University and other academic sources
Althoff & Reichardt
Economic Growth
Measured as "Wage bill" which is a long term projection for average wage × employment. It's the total labor income flowing to an occupation
Medium Demand
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
Growth Percentile:
Annual Openings:
Annual Openings Pct:
Analysis of Current AI Resilience
Loan Interviewers/Clerks
Updated Quarterly • Last Update: 2/17/2026

What's changing and what's not
Many routine clerical jobs in lending are already done by software. For example, banks use automated “underwriting” programs (like Fannie Mae’s Desktop Underwriter) to check loan applications quickly [1]. New AI tools are adding to this.
One news report describes a ChatGPT-based system that bilingual loan officers use to match Hispanic homebuyers with lenders and explain the rules in Spanish [2] [2]. In practice, this means computers can pull together data and even answer basic questions for customers. Official job data shows clerks “record applications” and “prepare and type” documents on computers [1], and AI is making those tasks faster.
In short, work like data entry, form-filling, and checking numbers is increasingly automated, while humans still handle complex or personal parts of the job.

AI in the real world
Even with these tools, banks will be cautious about replacing people completely. Loan clerks still must do a lot of talking and decision-making. The official job description puts core duties like “interview[ing] applicants” and “answer[ing] questions” about loans [1] [1].
Those parts need human judgment, empathy, and trust. Lenders also have strict rules to follow, so they tend to keep a person in charge of the final decisions. For example, in the AP story a loan officer said the AI tool “let him see requirements in one place” and speed up applications [2], but he himself still reviewed each case.
Overall, AI can cut down on paperwork and speed things up, but personal skills – explaining options clearly and helping customers feel confident – remain very important. This means young workers should learn both the tech tools and the human skills (like listening and explaining) to succeed in these jobs [2] [1].

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Median Wage
$48,950
Jobs (2024)
177,600
Growth (2024-34)
-2.3%
Annual Openings
13,300
Education
High school diploma or equivalent
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
AI-generated estimates of task resilience over the next 3 years
Answer questions and advise customers regarding loans and transactions.
Interview loan applicants to obtain personal and financial data and to assist in completing applications.
Accept payment on accounts.
Calculate, review, and correct errors on interest, principal, payment, and closing costs, using computers or calculators.
Order property insurance or mortgage insurance policies to ensure protection against loss on mortgaged property.
Contact credit bureaus, employers, and other sources to check applicants' credit and personal references.
Contact customers by mail, telephone, or in person concerning acceptance or rejection of applications.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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