Finance

Credit Analyst

Based on 36 assessments

35% Moderate risk

Average realistic automation risk across all Credit Analyst profiles in the dataset.

Raw potential
63%
Realistic risk
35%
Research benchmark ?
56%

Raw potential = I/O automation ceiling. Realistic risk = adjusted for informal knowledge and social context. Research benchmark: Eloundou et al. (2023)

Distribution across 36 profiles. Middle half of Credit Analysts score between 32% and 38%.

0% 50% 100%
p10 · 27%
44% · p90
On-screen work 56%

Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.

In-person + screen 23%

Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.

Computer + action 0%

Computer input, real-world output — needs someone to act on it, not just software.

Fully in-person 21%

No computer required. Furthest from automation — the strongest human advantage.

3 synthetic profiles for a Credit Analyst, ordered by automation exposure. Tab between them to see how task mix drives the score difference.

Task Time Type Exposure
Collaborating with underwriters or senior credit analysts to discuss complex cases, refine risk models, or align on credit policies and thresholds.
deep expertise
20% AA 4%
Preparing detailed credit reports summarizing financial analysis, risk assessments, and recommendations for approval, rejection, or conditional approval of credit applications.
deep expertise social element
19% DD 27%
Communicating with loan officers, relationship managers, or clients to clarify financial data, explain credit decisions, or request additional documentation.
deep expertise
14% AA 0%
Reviewing and analyzing financial statements (balance sheets, income statements, cash flow statements) of businesses applying for credit to assess their financial health and repayment capacity.
12% DD 59%
Staying updated on industry trends, regulatory changes, and economic conditions that may impact credit risk or lending practices.
deep expertise social element
12% AD 18%
Gathering and verifying additional financial data from external sources (e.g., credit bureaus, market reports, industry benchmarks) to supplement internal information.
11% AD 22%
Monitoring the financial performance of existing borrowers by tracking key metrics (e.g., debt ratios, liquidity) and flagging early signs of distress or default risk.
9% DD 70%

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