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Occupation deep dive / O*NET-SOC 13-2041.00 / Last verified June 2026

Will AI replace credit analysts?

ILO 2025 places credit analysts in the high exposure gradient. Structured credit-data analysis, financial-ratio generation, and standard risk-report drafting are technically and contextually feasible for current generative AI plus long-established automated credit-scoring models; the durable tasks are relationship lending, non-standard and distressed-credit judgement, and the accountability that sits behind a lending decision.

AI impact on credit analysis jobs in 2025-2026

The direct answer: AI is changing credit analysis work at task level, not eliminating the occupation outright. ILO 2025 places credit analysts in the high generative-AI exposure gradient, 2 of the top 5 O*NET tasks are classified displaceable, and BLS projects employment to follow its published outlook through 2034.

ILO 2025 exposure

HighFour-band gradient, refined index

Displaceable top tasks

2 of 5Brookings 2024 task rubric

BLS 2024-2034

Slower than averageSlower than average, projected employment change

Will credit analysts jobs grow or shrink by 2034?

The BLS Employment Projections 2024-2034 put credit analysts at Slower than average, classified slower than average. This is the official US decade projection from the National Employment Matrix, distinct from the ILO 2025 AI-exposure gradient above. Source: BLS Employment Projections 2024-2034.

personalise this exposure

The ILO national-average exposure for Credit Analysts is 70%. Adjust the four inputs below to see how your specific role characteristics shift the number up or down.

Years in this kind of role

5 years

Your current AI-tool usage

% of work that is routine / repeatable

50%

% of work requiring judgement / relationships

30%

HIGH EXPOSURE

66%

personalised AI exposure score ยท -4% vs ILO baseline (70%)

adjustment breakdown

Years experience adjustment0%
AI tooling (moderate)-4%
Routine work share0%
Judgement / relational work share0%

Heavy AI tooling adoption reduces personalised exposure (you're already augmenting). Routine fractions above 50% raise exposure. Years of experience modestly insulate (institutional knowledge, judgement). Judgement / relational fractions reduce exposure most. The model adjusts the ILO baseline by these factors; treat as a personalised reading, not a precise forecast.

Panel 1 / Exposure

High exposure

LOWMODERATEHIGHVERY HIGHILO 2025 EXPOSURE GRADIENT

ILO 2025 places credit analysts in the high exposure gradient. Structured credit-data analysis, financial-ratio generation, and standard risk-report drafting are technically and contextually feasible for current generative AI plus long-established automated credit-scoring models; the durable tasks are relationship lending, non-standard and distressed-credit judgement, and the accountability that sits behind a lending decision.

Source: ILO 2025 refined Generative AI Occupational Exposure Index. ISCO-08 mapping 2413. View methodology.

Panel 2 / Tasks

Top tasks for this role

  • Analyse credit data and financial statements to determine the degree of risk involved in extending credit or lending money.

    AI accelerates credit-data analysis and risk assessment; final risk judgement and accountability remain analyst-led.

  • Generate financial ratios, using computer programs, to evaluate customers' financial status.

    Programmatic ratio generation is technically and contextually feasible for current generative AI and is already automated in most lending stacks.

  • Prepare reports that include the degree of risk involved in extending credit or lending money.

    Standard-form credit-risk report drafting is technically and contextually feasible for current generative AI.

  • Complete loan applications, including credit analyses and summaries of loan requests, and submit to loan committees for approval.

    Application assembly and summary drafting are heavily AI-augmented; committee-facing accountability remains human.

  • Analyse financial data, such as income growth, quality of management, and market share, to determine expected profitability of loans.

    Qualitative judgement on management quality and forward profitability is augmentation-prone and grows as AI handles the routine data assembly.

Source: O*NET 30.2 task list (CC-BY 4.0); Brookings 2024 task-level rubric. View methodology.

Panel 3 / What is growing

Growth and skills outlook

BLS 2024-2034

Slower than average

no published figure projected change (no published figure jobs).

WEF 2025 / Top growing skills relevant to this role

  • AI and big data (Technology)
  • Analytical thinking (Cognitive)
  • Technological literacy (Technology)

Brookings 2024 places credit analysis among the more-exposed financial functions: routine analysis and report writing are exposed, while distressed-credit judgement, relationship lending, and lending accountability are augmentation-prone.

Source: BLS Employment Projections 2024-2034; WEF Future of Jobs Report 2025. View methodology.

What this occupation does

Credit analysts analyse credit data and financial statements of individuals or firms to determine the degree of risk involved in extending credit or lending money. The role spans financial-ratio analysis, risk scoring, loan-application review, credit-report writing, and recommendations to loan committees across commercial and consumer lending.

The exposure score in context

The ILO 2025 refined Generative AI Occupational Exposure Index places credit analysts in the high exposure gradient. ILO 2025 places credit analysts in the high exposure gradient. Structured credit-data analysis, financial-ratio generation, and standard risk-report drafting are technically and contextually feasible for current generative AI plus long-established automated credit-scoring models; the durable tasks are relationship lending, non-standard and distressed-credit judgement, and the accountability that sits behind a lending decision.

The mapping uses ISCO-08 code 2413 (BLS-published SOC-to-ISCO crosswalk). The full methodology, including the dominant-match rule for one-to-many crosswalks, is at /methodology/#algorithm.

The top five tasks, classified

The top five O*NET 30.2 tasks for this occupation, each tagged Displaceable / Changing / Growing per the Brookings 2024 task-level rubric. The tag definitions are at /glossary/#displaceable-task, /glossary/#changing-task, and /glossary/#growing-task.

  1. Changing: Analyse credit data and financial statements to determine the degree of risk involved in extending credit or lending money. AI accelerates credit-data analysis and risk assessment; final risk judgement and accountability remain analyst-led.
  2. Displaceable: Generate financial ratios, using computer programs, to evaluate customers' financial status. Programmatic ratio generation is technically and contextually feasible for current generative AI and is already automated in most lending stacks.
  3. Displaceable: Prepare reports that include the degree of risk involved in extending credit or lending money. Standard-form credit-risk report drafting is technically and contextually feasible for current generative AI.
  4. Changing: Complete loan applications, including credit analyses and summaries of loan requests, and submit to loan committees for approval. Application assembly and summary drafting are heavily AI-augmented; committee-facing accountability remains human.
  5. Growing: Analyse financial data, such as income growth, quality of management, and market share, to determine expected profitability of loans. Qualitative judgement on management quality and forward profitability is augmentation-prone and grows as AI handles the routine data assembly.

What is growing in this role

The BLS Employment Projections 2024-2034 outlook for credit analysts is slower than average. Source: BLS Employment Projections 2024-2034.

Per the WEF Future of Jobs Report 2025, the top three growing skills relevant to this role are: AI and big data, Analytical thinking, Technological literacy. The skills are mapped to the occupation's O*NET skills profile.

Brookings 2024 places credit analysis among the more-exposed financial functions: routine analysis and report writing are exposed, while distressed-credit judgement, relationship lending, and lending accountability are augmentation-prone.

Credit analysts and the shift to automated credit decisioning

Credit analysis is among the most structured knowledge tasks in finance: the core work turns financial statements and credit data into ratios, risk grades, and a standard-form recommendation. That structure is exactly what current generative AI plus long-established automated credit-scoring models handle well, which is why the top O*NET tasks for the role skew displaceable and changing rather than growing.

The BLS does not cover credit analysts in detail in the Occupational Outlook Handbook, but the underlying employment data classifies the outlook as below average, and O*NET reports a median annual wage of $83,510 for the occupation (2024). The durable part of the job is the judgement automated scoring cannot own: distressed and non-standard credits, relationship and covenant negotiation, and the accountability a named analyst carries when a lending decision is challenged.

Sources: O*NET OnLine 13-2041.00 (Credit Analysts); My Next Move / O*NET (median wage and outlook, 2024).

Similar occupations

O*NET 30.2 lists the following related roles. Each links to its own deep dive where one is published.

Industry context

This role sits primarily in the Finance industry. The industry-level rollup includes the cross-occupation exposure profile and the BLS-published industry-level outlook.

How this assessment was made

The full methodology is at /methodology/: ILO 2025 refined index for the gradient, Brookings 2024 rubric for the task tags, BLS 2024-2034 for the growth outlook, WEF 2025 for the skills demand. The pre-empted critiques are at /how-to-argue-with-this/.

AI impact on credit analysis jobs: frequently asked questions

Will AI replace credit analysts in 2025-2026?

Not outright. The ILO 2025 refined Generative AI Occupational Exposure Index places credit analysts in the high exposure gradient, and 2 of the top 5 O*NET 30.2 tasks are classified displaceable under the Brookings 2024 task rubric, with the rest changing or growing. AI is changing credit analysis work at task level in 2025-2026 rather than eliminating the occupation.

Are credit analysis jobs growing or declining?

The US Bureau of Labor Statistics projects employment for credit analysts to follow its published BLS outlook (slower than average) between 2024 and 2034. Source: BLS Employment Projections 2024-2034, National Employment Matrix.

Which credit analysis tasks are most exposed to AI?

The most-exposed top tasks, classified displaceable under the Brookings 2024 rubric, are: generate financial ratios, using computer programs, to evaluate customers' financial status; prepare reports that include the degree of risk involved in extending credit or lending money.

What skills are growing for credit analysts?

Per the WEF Future of Jobs Report 2025, the top growing skills relevant to this role are AI and big data, Analytical thinking, Technological literacy.

From the cluster