Unit 1298: Advanced Actuarial Modeling Techniques

1. Introduction to Advanced Actuarial Models

• Overview of advanced actuarial modeling
• Key concepts: model selection, data preparation, and evaluation criteria
• Types of actuarial models and their applications

2. Generalized Linear Models (GLMs) in Actuarial Science

• Theoretical foundations of GLMs
  • Exponential family distributions
  • Link functions
• Model fitting techniques
  • Maximum likelihood estimation
  • Diagnostics and goodness-of-fit
• Interpretation of GLM results in insurance contexts
• Case studies: pricing, reserving, and risk classification

3. Bayesian Statistics in Actuarial Modeling

• Principles of Bayesian inference
• Prior distributions and elicitation
• Posterior inference and updating with data
• Bayesian model selection and comparison
• Computational methods: Markov Chain Monte Carlo (MCMC) basics
• Applications in credibility theory, reserving, and risk assessment

4. Time Series Analysis for Actuarial Purposes

• Fundamentals of time series data
• Autoregressive (AR) models
• Moving average (MA) models
• ARMA and ARIMA modeling
• Time series diagnostics and model validation
• Forecasting techniques for actuarial applications

5. Survival Analysis and Actuarial Applications

• Introduction to survival and time-to-event data
• Kaplan-Meier estimation methods
• Cox proportional hazards model
• Parametric survival models
• Applications in life insurance, annuities, and risk management

6. Machine Learning Techniques in Actuarial Modeling

• Overview of machine learning in actuarial science
• Decision trees and random forests
• Neural networks and deep learning basics
• Support vector machines (SVMs)
• Model training, validation, and overfitting avoidance
• Use cases in predictive modeling and risk classification

7. Long-Term Care Modeling

• Multi-state models for long-term care insurance
• Disability insurance modeling approaches
• Policyholder behavior modeling and analysis
• Valuation and risk assessment for long-term care products

8. Economic Scenario Generators for Asset-Liability Management

• Role of economic scenario generators (ESGs)
• Stochastic modeling of financial markets
• Interest rate modeling and risk assessment
• Scenario generation techniques
• Risk aggregation and portfolio management

9. Model Validation and Regulatory Compliance

• Importance of model validation in actuarial practice
• Regulatory frameworks and standards
• Stress testing and scenario analysis
• Sensitivity analysis techniques
• Documentation and audit trails
• Best practices for ensuring model reliability