Actuarial analysts spend countless hours building models, writing reports, and communicating complex risk findings to non-technical stakeholders. AI tools like ChatGPT can dramatically reduce the time spent on repetitive documentation, data interpretation, and communication tasks. These 35 prompts are designed to slot directly into your daily workflow — from mortality table analysis to regulatory filings.
1. Data Analysis and Interpretation
I have a mortality table with the following qx values for ages 60–70: [paste data]. Identify any unusual patterns or deviations from standard industry tables (e.g., SOA 2014 VBT) and suggest possible explanations.
Explain the following loss development triangle data to a non-actuarial CFO: [paste triangle]. Highlight key trends in paid vs. incurred losses and what they imply for reserve adequacy.
I ran a GLM for personal auto pricing with the following output: [paste coefficients and p-values]. Summarize which rating factors are statistically significant and how I should interpret the interaction terms.
Given the following experience study results comparing actual vs. expected mortality for a life insurance block: [paste A/E ratios by age band], draft a one-page narrative explaining the findings and their implications for assumption setting.
I have 10 years of workers' compensation claim frequency and severity data by industry class: [paste data]. Identify trend patterns and suggest appropriate trend factors for next year's rate filing.
2. Report Writing and Documentation
Write an executive summary for an actuarial valuation report on a pension plan. Key findings: funded status is 82%, the discount rate used is 4.5%, and the plan sponsor needs to increase contributions by $2.3M annually. Audience: board of trustees with limited actuarial knowledge.
Draft the assumptions section of an actuarial memorandum for a property & casualty reserve review. Include standard language for loss development factors, tail factors, and trend assumptions. Flag where I should insert specific values.
Write a clear, plain-English description of the appointed actuary's role and responsibilities for inclusion in an annual statement filing. Ensure it meets the tone and formality expected by state insurance regulators.
I need to document my methodology for calculating IBNR reserves using the Bornhuetter-Ferguson method. Write a step-by-step methodology section suitable for an internal actuarial report, including formulas and variable definitions.
Draft a limitations and caveats section for an actuarial opinion letter on a captive insurance company. Cover data quality limitations, model uncertainty, and reliance on management-provided information.
3. Model Validation and Peer Review
I am peer-reviewing a pricing model for a commercial umbrella product. Generate a checklist of 15 critical items I should verify, covering data inputs, rating algorithm logic, actuarial assumptions, and regulatory compliance.
Explain three common sources of model risk in a stochastic mortality projection model (e.g., Lee-Carter) and suggest specific tests I can perform to quantify and document each risk.
I need to validate a loss reserving model built by a junior analyst. What questions should I ask to understand their methodology, and what diagnostic tests (e.g., residual plots, back-testing) should I request they run?
Describe a structured approach for back-testing an economic capital model over the past five accident years. What metrics should I use to assess model performance, and what deviation thresholds should trigger a model update?
Generate a list of stress scenarios I should apply to a longevity risk model for an annuity portfolio to test its robustness. Include both historical scenarios (e.g., COVID-19 mortality shock) and hypothetical extreme scenarios.
4. Regulatory and Compliance Communication
Summarize the key actuarial requirements under ASOP No. 25 (Credibility Procedures) in plain language, and explain how I should document my credibility weighting decisions in a rate filing for a small commercial lines book.
Draft a response to a state DOI objection letter that questioned our selected loss development factors as being too aggressive compared to industry benchmarks. Our position is that our book has superior loss control programs that justify the selection.
Write a clear explanation of the difference between statutory reserves and GAAP reserves for a non-actuarial compliance officer preparing for a state market conduct examination.
I need to prepare talking points for a meeting with our state insurance regulator about our rate increase filing. The requested increase is 12.4% on a homeowners book. Draft three to four key messages that explain the actuarial justification without being overly technical.
Explain the principles-based reserving (PBR) requirements under VM-20 to a new actuarial analyst joining our life insurance team. Cover the key components, how it differs from formulaic reserves, and what additional work is required under PBR.
5. Stakeholder Communication
Translate the following actuarial finding into a two-paragraph summary for a C-suite audience: our property cat model shows a 1-in-100-year loss of $450M, which exceeds our current reinsurance attachment point of $380M by $70M.
I need to present reserve development results to the audit committee. The reserve strengthening is $15M, driven by adverse development in our commercial auto line. Write a five-bullet talking points summary that is honest but does not cause undue alarm.
Draft an email to a client explaining why their workers' compensation experience modification factor increased from 0.92 to 1.15 this year. Use simple language and avoid actuarial jargon. Suggest two actions they can take to improve it.
Write a one-page FAQ document answering the five most common questions employees ask about their defined benefit pension plan — covering benefit calculations, vesting, survivor benefits, and what happens if the company is acquired.
I need to explain Value at Risk (VaR) and Tail Value at Risk (TVaR) to a newly hired risk manager with a finance background but no actuarial training. Write a concise explanation with a simple numerical example.
6. Research and Assumption Development
Summarize the key findings from the SOA's most recent mortality improvement scale (MP-2023 or latest available) and explain how I should incorporate it into pension plan valuations compared to using a static mortality table.
I am developing lapse rate assumptions for a universal life insurance product. Describe the key policyholder behavior drivers I should investigate, what data sources to use, and how to structure a credibility-weighted assumption.
Outline a research plan for benchmarking our commercial property loss ratios against industry data. Specify which external data sources (e.g., SNL, A.M. Best, NAIC) I should use and how to adjust for differences in territory, deductible, and coverage mix.
Explain the difference between parameter risk, process risk, and model risk in the context of P&C loss reserving. For each risk type, give one practical example from a workers' compensation book of business.
I need to set a claims inflation assumption for a long-tail liability line. Walk me through the key economic and line-specific factors I should consider, and how to distinguish between social inflation and pure medical cost inflation.
7. Career Development and Study Support
I am preparing for the CAS Exam 5 (Basic Ratemaking and Reserving). Create a two-week study plan covering the key syllabus topics, with specific study techniques for the more mathematically intensive sections.
Explain the chain-ladder (development) method for estimating IBNR reserves as if you are tutoring a student preparing for actuarial Exam 6. Include a worked numerical example with a 3x3 development triangle.
I am a credentialed ACAS looking to move from personal lines pricing to enterprise risk management. What technical skills and credentials (e.g., CERA) should I prioritize, and how should I reframe my pricing experience on my resume?
Generate 10 behavioral interview questions that are commonly asked when interviewing for a senior actuarial analyst role at a large P&C insurer, along with guidance on how to structure strong STAR-method answers.
I want to improve my R programming skills for actuarial data analysis. Create a 30-day learning plan that starts from intermediate R knowledge and progresses to building GLM pricing models and visualizing loss development triangles.
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Works with ChatGPT, Claude, and DeepSeek.
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