F70RT Risk Theory

Dr Seva ShneerMarjan Qazvini

Course co-ordinator(s): Dr Seva Shneer (Edinburgh), Marjan Qazvini (Malaysia).


This course aims:

  • to introduce and apply the statistical techniques used in the analysis of general insurance processes, including models for aggregate claims and simple reinsurance arrangements;
  • to examine the assessment of premiums for short term insurance contracts;
  • to introduce experience rating (a) using Bayesian credibility theory, and (b) in the context of no claims discount systems;
  • to introduce classical ruin theory;
  • to examine claims reserving through the use of run-off triangles;
  • to cover the basics of simulation.


  • Conditional expectation and compound distributions
  • Loss distributions
  • Aggregate risk model and Individual risk model
  • Risk sharing – simple reinsurance and deductibles
  • Premium calculation principles
  • Bayesian estimation and Credibility Theory
  • Experience rating – No Claims Discount systems
  • Ruin theory
  • Claims reserving – run-off triangles
  • Simulation

Detailed Information

Pre-requisite course(s): F79MA Statistical Models A (Project Course) .

Location: Edinburgh.

Semester: 2.


The detailed syllabus is given in the workbook. There is also a link to it on the course webpage.

Learning Outcomes: Subject Mastery

A detailed list of the learning outcomes is given on the course webpage.

Learning Outcomes: Personal Abilities

At the end of the course, students should be able to:

    • Demonstrate the ability to learn independently
    • Manage time work to deadlines and prioritise workloads
    • Use an appropriate computer package to process data
    • Present results in a way which demonstrates that they have understood the technical and broader issues of risk theory

Reading list:

A substantial spiral-bound workbook is given to each student – it contains core lecture material, worked examples, illustrations, and all tutorials.

Assessment Methods:

2 hour examination at the summer diet.

SCQF Level: 10.

Credits: 15.

Other Information

Help: If you have any problems or questions regarding the course, you are encouraged to contact the lecturer

VISION: further information and course materials are available on VISION