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Actuary

Finance AI-Augmented

Uses mathematics, statistics, and financial theory to assess the risk of potential events and help businesses minimize cost of risk.

B
🔵 Stable
Actuary has a positive outlook with moderate hiring activity. A reliable path with room to grow.
79
/ 100
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Work Profile

Stress
4/10
Work-Life
9/10
Future Outlook
8/10
Hours / Week
40

Salary Growth

Starting
$85,000
Year 5
$125,000
Year 10
$165,000
Top Earners
$280,000
Promotion Path: Actuarial Analyst > Associate > Fellow > Chief Actuary

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Core Skills and Tools

These are the practical tools, systems, math, and AI skills used in Actuary roles.

AI & Automation

Actuarial Process Automation

Core Skills

Actuarial Pricing
Loss Reserving
Reinsurance Analysis
Cash Flow Modeling
Assumption Development
Capital Management Support
Rate Indication Development
Stakeholder Results Communication

Industry Knowledge

Property Casualty Reserving
Life Reinsurance Pricing
Regulatory Filing Exhibits
Asset Liability Management

Math & Analysis

IBNR Calculation
Chain Ladder Modeling
Bornhuetter Ferguson Modeling
Experience Study Analysis

Requirements

Bachelor's degree requirement
Degree field requirement
Professional certification

Systems & Software

Prophet Modeling
AXIS Model Development
Actuarial Modeling Software
Microsoft Excel

About to graduate?

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Other Potential Career Pivot Paths

Pivot paths coming soon for this career.

How to Get Hired

This section focuses on practical readiness: what skills matter, what tools or certifications may help, and what you can do now to become more employable.

Unlock the Full Getting Hired Plan

See the exact skills, certifications, projects, and step-by-step plan to break into Actuary.

  • Certifications that actually help
  • Real projects to build experience
  • A 30–60 day action plan
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AI Impact & Task Breakdown

AI-Augmented

AI automates data cleaning and basic modeling, allowing actuaries to focus on complex risk scenarios and strategy.

How to Stay Valuable

  • Develop judgment, communication, and problem-solving skills
  • Learn how AI tools can support this career instead of ignoring them
  • Move toward strategy, interpretation, and higher-value work over time

AI Scores

Automation Risk: 4.8/10 Human Value: 8.4/10 AI Leverage: 7.8/10

Based on 10 analyzed tasks

More likely automated

  • Build loss projection models
  • Perform valuation and reserving analysis

Still requires human judgment

  • Present recommendations to business leaders
  • Set pricing assumptions

How AI Affects This Job

This career includes a mix of tasks. Some are becoming more automated, while others are becoming more valuable because they require human expertise.

Build loss projection models

Develop models that estimate future claims costs reserves and profitability for insurance products using historical experience and assumptions

Moderate Automation High Human Value High AI Leverage
Automation: 6/10 • AI Leverage: 9/10 • Human Value: 8/10

Likely adoption: 0-2 years

Model Financial Risk

Build models that estimate loss frequency severity and long term financial exposure

Moderate Automation High Human Value High AI Leverage
Automation: 5/10 • AI Leverage: 8/10 • Human Value: 8/10

Likely adoption: 0-2 years

Set pricing assumptions

Analyze claim frequency severity lapse behavior and expenses to recommend pricing assumptions for new or renewed products

Moderate Automation High Human Value High AI Leverage
Automation: 5/10 • AI Leverage: 8/10 • Human Value: 9/10

Likely adoption: 3-5 years

Develop Pricing Assumptions

Set assumptions for rates reserves and forecasts using statistical and business inputs

Moderate Automation High Human Value High AI Leverage
Automation: 5/10 • AI Leverage: 8/10 • Human Value: 8/10

Likely adoption: 3-5 years

Perform valuation and reserving analysis

Calculate policy liabilities assess reserve adequacy and document methodology for financial reporting and regulatory review

Moderate Automation High Human Value High AI Leverage
Automation: 6/10 • AI Leverage: 8/10 • Human Value: 8/10

Likely adoption: 0-2 years

Review Regulatory Requirements

Interpret rules and standards affecting filings disclosures and actuarial methods

Moderate Automation High Human Value High AI Leverage
Automation: 4/10 • AI Leverage: 7/10 • Human Value: 8/10

Likely adoption: 0-2 years

Run risk and scenario testing

Stress test portfolios under alternative economic mortality catastrophe or policyholder behavior scenarios to quantify risk exposure

Moderate Automation High Human Value High AI Leverage
Automation: 5/10 • AI Leverage: 9/10 • Human Value: 8/10

Likely adoption: 3-5 years

Present Findings to Leadership

Explain model results and business implications to finance underwriting and executives

Moderate Automation High Human Value
Automation: 4/10 • AI Leverage: 6/10 • Human Value: 9/10

Likely adoption: 3-5 years

Present recommendations to business leaders

Explain pricing reserve or capital impacts to underwriting finance and executives and defend assumptions behind recommendations

Low Automation Risk High Human Value High AI Leverage
Automation: 3/10 • AI Leverage: 7/10 • Human Value: 10/10

Likely adoption: 5-10 years

Monitor Portfolio Performance

Compare actual results to projections and recommend adjustments to models or strategy

Moderate Automation High Human Value High AI Leverage
Automation: 5/10 • AI Leverage: 8/10 • Human Value: 8/10

Likely adoption: 0-2 years

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