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Finance

Financial Analyst

Based on 36 assessments

52% High risk

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

Raw potential
81%
Realistic risk
52%
Research benchmark ?
50%

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 Financial Analysts score between 48% and 55%.

0% 50% 100%
p10 · 46%
59% · p90
On-screen work 88%

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

In-person + screen 0%

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 12%

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

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

Task Time Type Exposure
Building and maintaining financial models (e.g., forecasting, valuation, scenario analysis) in spreadsheets or specialized software to predict future performance
24% DD 49%
Analyzing financial statements (income statement, balance sheet, cash flow) to assess company performance and identify trends or anomalies
deep expertise
20% DD 36%
Meeting with stakeholders (e.g., managers, clients, or team members) to discuss financial performance, explain analysis, or gather additional context for projects
deep expertise
16% AA 4%
Monitoring market trends, economic indicators, and industry news to stay informed about factors that could impact financial analysis or recommendations
14% DD 53%
Preparing reports and presentations (e.g., quarterly earnings summaries, investment recommendations) for management or clients, summarizing findings and insights
12% DD 48%
Collecting and organizing financial data from various digital sources (e.g., company databases, market reports, ERP systems) to prepare for analysis
6% DD 86%
Reviewing and validating data inputs or model outputs for accuracy, often by cross-referencing with colleagues or external sources
deep expertise social element
4% DD 32%

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