Risk Insurance¶
Year 2 · Block 2b · Actuarial science
Coverage rules and portfolio models lead to insurance-data estimation, decisions under risk, premium principles and experience rating.
- 14 lectures
- 52 concept pages
Practise¶
Lectures¶
1Insurance coverage: transforms and mixed losses4 concepts
- Cumulant Generating Function
- Mixed Discrete and Continuous Loss Distribution
- Ordinary Deductible
- Probability Generating Function
Review lecture 1 in Concept Finder 4 concepts
2Insurance coverage: deductibles and limits5 concepts
- Franchise Deductible
- Pareto Loss Model
- Stop-Loss Transform and Reinsurance
- Loss Elimination Ratio
- Policy Limit
Review lecture 2 in Concept Finder 5 concepts
3Coverage completion and portfolio risk models3 concepts
Review lecture 3 in Concept Finder 3 concepts
4Compound risks and likelihood foundations6 concepts
- Compound Risk Distribution
- Maximum Claim in a Portfolio
- Maximum Likelihood Estimation
- Compound Poisson Distribution
- Compound Poisson Process
- Superposition of Compound Poisson Risks
Review lecture 4 in Concept Finder 6 concepts
5Special observation mechanisms and GLM foundations5 concepts
- Exponential Family
- Generalized Linear Model
- Likelihood for Censored Loss Data
- Likelihood for Grouped Loss Data
- Likelihood for Truncated Loss Data
Review lecture 5 in Concept Finder 5 concepts
6Claim-frequency GLMs and rating factors5 concepts
- Information Criteria for Risk Models
- Poisson Regression
- Exposure Offset in Claim-Frequency Models
- Overdispersion in Count Models
- Rating Factors and Interactions in Insurance GLMs
Review lecture 6 in Concept Finder 5 concepts
7Utility theory and risk aversion2 concepts
Review lecture 7 in Concept Finder 2 concepts
8Insurance decisions and stochastic order2 concepts
Review lecture 8 in Concept Finder 2 concepts
9Tail comparisons and stop-loss order3 concepts
Review lecture 9 in Concept Finder 3 concepts
10Dispersion, utility dominance and exponential order3 concepts
Review lecture 10 in Concept Finder 3 concepts
11Risk-order consequences and premium foundations4 concepts
- Premium Principles and Their Properties
- Risk Orders Under Aggregation
- Stop-Loss Separation Theorem
- Expected Value Premium Principle
Review lecture 11 in Concept Finder 4 concepts
12Premium principles and bonus-malus foundations5 concepts
- Bonus-Malus System
- Exponential Premium Principle
- Standard Deviation Premium Principle
- Variance Premium Principle
- Zero-Utility Premium
Review lecture 12 in Concept Finder 5 concepts
13Bonus-malus dynamics and reporting incentives3 concepts
Review lecture 13 in Concept Finder 3 concepts
14Bonus-malus efficiency and premium scales2 concepts
Review lecture 14 in Concept Finder 2 concepts
Concepts appear in the lecture that introduces them, foundations first. A course name after a concept marks a page from another course used that lecture.
More about this course¶
Before you startEarlier concepts these pages use most. If a step feels unfamiliar, revisit them first.4 courses
AchievementsCourse challenges and how many learners hold them
How to read this courseNotation, shared pages and conventions
These notes introduce course-specific concepts. Existing Year 1 concepts have one canonical page and are linked under Before you start. The lecture sequence follows the 2026 course outline: 14 lectures across seven teaching weeks, numbered by class, with no lectures in course Week 5. Concepts appear at their first introduction and are reused by links afterwards. The stochastic-dominance pages state their loss-versus-wealth convention explicitly.
SourcesCourse material these pages were checked against
- Risk Insurance · Course outline (2026)
- Risk Insurance · Lectures 1–14
For teachers and tutorsPrepare the connections for your next explanation
Choose a concept for your next explanation. Review its recorded foundations and later uses, then check the concept page's sources against your own course material.
The workbench uses published prerequisite links. It describes concept relationships; class performance and teaching coverage need separate evidence.
Aliases: RI
Last updated: 26 October 2026 00:09