Best ChatGPT prompts for Actuaries

Given a dataset of 10,000 policyholders with 15 variables each, including age, location, and claim history, and assuming a 5% annual increase in claims frequency, develop a generalized linear model to predict future claims costs, then validate this model against a holdout sample of 2,000 policyholders, providing a detailed report on the model's performance metrics, such as mean squared error and R-squared, and outlining steps to further improve model accuracy and reduce error rates to meet the 95% quality assurance benchmark.

For a block of 5,000 term life insurance policies with issue ages ranging from 25 to 60, and assuming a mortality table based on the SOA 2015 Valuation Basic Table with a 2% annual interest rate, calculate the gross and net reserves using the Full Preliminary Term (FPT) reserve method, considering a 10% reserve strengthening due to adverse experience, and provide a detailed breakdown of the reserve calculations by policy year and age, including sensitivity analyses to assess the impact of varying interest rates and mortality assumptions on reserve levels and error rates.

Under the Solvency II framework, calculate the solvency capital requirement (SCR) for a non-life insurance portfolio consisting of motor, property, and liability lines, using the standard formula approach with a 99.5% confidence level over a one-year time horizon, and considering a correlation matrix between risk modules, then analyze the impact of different stress scenarios on the SCR, including a 20% increase in claims frequency and a 15% decrease in investment returns, providing recommendations to optimize capital allocation and minimize error rates in accordance with quality assurance protocols.

Conduct an experience study on a workers' compensation insurance book of business, analyzing the past 5 years of loss data to determine trends in frequency and severity, and using generalized linear modeling to forecast future losses, then develop rate indications for the upcoming policy year, considering changes in regulatory requirements, economic conditions, and industry trends, and providing a detailed report on the study's findings, including any necessary rate adjustments and the rationale behind them, to inform the pricing model and meet quality assurance standards.