## Syllabus **Content Outline** [2025 Exam 7 - Content Outline](https://www.casact.org/sites/default/files/2023-05/Exam7_Content_Outline.pdf) ## Domains Estimation of Claim Liabilities 1. Data Preparation, Organization, & Analysis 2. Unpaid Claim Point Estimates 3. Unpaid Claim Stochastic Distributions 4. Unpaid Claim Output & Diagnostic Analysis 5. Reinsurance ## Sources | Source | Coverage | | ------------------------------------------------------------------------------------------------------------- | ----------------------- | | Loss Development Using Credibility - Brosius (1993) | A1-A3,<br>A6, A11 | | LDF Curve Fitting and Stochastic Reserving:<br>A Maximum Likelihood Approach - Clark (2003) | A2-A3,<br>A6-A8,<br>A11 | | Reserving for Reinsurance - Friedland (2022) | A15-A17 | | Credible Loss Ratio Claims Reserves:<br>The Benktander, Neuhaus and Mack Methods Revisited - Hürlimann (2009) | A1-A3,<br>A6, A11 | | ... see more | | ## Tasks | Domain | Task | | ------------------------------------------ | -------------------------------------------------------------------------------------------------------------- | | Data Preparation, Organization, & Analysis | Perform data diagnostic analyses and adjust for data issues | | Unpaid Claim Point Estimates | Calculate unpaid claims estimates | | Unpaid Claim Point Estimates | Test unpaid claims estimates for reasonableness | | Unpaid Claim Point Estimates | Estimate unpaid claims for various layers of coverage | | Unpaid Claim Point Estimates | Forecast premium reserves (e.g., reserves for retrospective premiums)<br>Unpaid Claim Stochastic Distributions | | Unpaid Claim Stochastic Distributions | Estimate parameters of unpaid claims distributions | | Unpaid Claim Stochastic Distributions | Calculate the moments and percentiles of unpaid claim distributions | | Unpaid Claim Stochastic Distributions | Simulate parameter percentiles and unpaid claims percentiles | | Unpaid Claim Stochastic Distributions | Calculate the mean and prediction error of a reserve | | Unpaid Claim Stochastic Distributions | Derive predictive distributions using stochastic methods<br>Unpaid Claim Output & Diagnostic Analysis | | Unpaid Claim Output & Diagnostic Analysis | Test output of unpaid claim distributions for reasonableness | ### Terms | **Term** | **Definition** | | ------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------- | | [[Diagnostic Analysis]] | | | [[Unpaid Claims Liabilities]] | The estimated amount required to cover claims that have been incurred but not yet paid. | | [[Loss Development Factors (LDF)]] | Multiplicative factors used to project incurred or paid losses to their ultimate value. | | [[Chain Ladder Method]] | A reserving method that uses historical loss development patterns to project future claims liabilities. | | [[Benktander Method]] | A credibility-weighted method between the Chain Ladder and Bornhuetter-Ferguson approaches for reserve estimation. | | [[Bootstrap Model]] | A statistical method that uses resampling to estimate the variability of reserve estimates. | | [[Bayesian MCMC Model]] | A method that applies Bayesian statistics and Markov Chain Monte Carlo techniques to estimate claim reserves. | | [[Generalized Linear Model (GLM)]] | A flexible statistical model used for predicting claim reserves and other actuarial applications. | | [[Credibility Theory]] | A statistical approach that blends past data with external information to improve prediction accuracy. | | [[Stochastic Reserving]] | A reserving approach that incorporates randomness and probability distributions into claim liability estimates. | | [[Risk Margins]] | Additional reserves added to account for uncertainty in claim liabilities. | | [[Reinsurance]] | A risk transfer mechanism where an insurer transfers portions of its risk to another insurer (the reinsurer). | | [[Ceded Loss Reserves]] | The portion of unpaid claim reserves that is transferred to a reinsurer. | | [[Retrospective Rating]] | A type of insurance pricing where premiums are adjusted based on actual loss experience during the policy period. | | [[Data Diagnostics]] | The process of analyzing data quality, detecting errors, and making necessary adjustments before applying actuarial models. | | [[Predictive Distributions]] | Probability distributions used to forecast potential future values of unpaid claims. | | [[Moments of a Distribution]] | Statistical measures (mean, variance, skewness, kurtosis) used to describe the shape of a probability distribution. | | [[Percentiles of a Distribution]] | Specific points in a probability distribution that indicate the likelihood of a claim reserve reaching a given level. | | [[Assumption Testing]] | Evaluating whether the underlying assumptions of reserving models are reasonable and valid. | | [[ODP Bootstrap Model]] | Overdispersed Poisson Bootstrap, a stochastic method for estimating reserve variability. | | [[Premium Reserves]] | Reserves set aside for unearned premiums or adjustments for retrospective-rated policies. | | [[Parameter Estimation]] | The process of determining key statistical parameters (such as mean and variance) for a reserving model. | | [[Simulation Techniques]] | Computational methods that generate multiple scenarios to estimate reserve variability and uncertainty. | | [[Testing for Reasonableness]] | Analyzing whether model outputs align with expectations based on experience and expert judgment. | | [[Actuarial Standards of Practice (ASOPs)]] | Guidelines that actuaries follow to ensure the appropriate use of methods and assumptions in their work. |