Actuarial Science

Definitive Guide to CS2 – Risk Modelling and Survival Analysis

risk modelling cs2

Core Principles

There are three main modules in the Core Principles stage: Actuarial Statistics (CS), Actuarial Mathematics (CM), and Business (CB). All of these modules need to be passed to be able to qualify as an Associate or a Fellow. To the right of each objective are the chapter numbers in which the objective is covered in the ActEd course. The aim of Subject CS2 is to provide a grounding in mathematical and statistical modeling techniques that are of particular relevance to actuarial work, including stochastic processes and survival models and their application.

On successful completion of this subject, a student will be able to:

  1. describe and use statistical distributions for risk modeling
  2. describe and apply the main concepts underlying the analysis of time series models
  3. describe and apply Markov chains and processes
  4. describe and apply techniques of survival analysis
  5. describe and apply basic principles of machine learning.

CS2 Syllabus & Assessment by IFOA

The subject CS2 Syllabus can be found here. The chapter numbers covering the objectives covered in the ActEd course are listed to the right of each objective.

Subject CS2’s goal is to provide a foundation in mathematical and statistical modeling approaches relevant to actuarial work, such as stochastic processes and survival models, as well as their application.

Competences

A student who successfully completes this topic will be able to: 

  1. define and use statistical distributions for risk modeling
  2. explain and apply the key ideas underpinning time series analysis
  3. explain and use Markov chains and processes
  4. explain and apply survival analysis approaches
  5. Explain and apply fundamental machine learning principles.

Syllabus topics

  1. Random variables and distributions for risk modeling (20%)
  2. Time series (20%)
  3. Stochastic processes (25%)
  4. Survival models (25%)
  5. Machine learning (10%)

The weightings represent the approximate balance of this subject’s assessment across the main syllabus subjects, as averaged over a number of examination sessions.

The weightings also correspond to the amount of learning material beneath each syllabus subject. However, this will also reflect factors such as the relative complexity of each issue, and thus the amount of explanation and assistance required for it. The necessity to give a comprehensive foundation understanding on which to develop the other objectives; the quantity of prior knowledge needed; and the degree to which each topic area is more knowledge or application focused.

CS2 Exam format

CS2 (Risk Modelling and Survival Analysis) expands on CS1.  It teaches statistical methods for risk modeling, time series analysis, stochastic processes (particularly Markov chains and Markov jump processes), survival analysis (including regression methods applied to duration data), and graduation approaches.  It also contains a high-level overview of machine learning. The course covers theory and applying concepts to real-world data sets using R. 

This subject’s material is applied to actuarial modeling in subjects CM1 and CM2.

You must sit A + B papers in the same session.

Risk Modelling and Survival Analysis (CS2) core reading is available from the IFoA E-Shop

From September 2021, an additional 5 minutes have been added to each paper to allow for candidates to download or print if required, their exam paper.

Also, Check – Registration Announcement for May 2023 Actuarial Exam

CS2 Course Content by IFOA

There are five parts to the Subject CS2 course. The parts cover related topics and are broken down

into chapters. At the end of each part, there are assignments testing the material from that part.

Following are the parts and chapters that relate to each other and how the chapters relate to the days of the regular tutorials. 

This list should help you plan your progress across the study session:

  1. Stochastic processes
  2. Markov chains
  3. The two-state Markov model and the Poisson model
  4. Time-homogeneous Markov jump processes
  5. Time-inhomogeneous Markov jump processes
  6. Survival models
  7. Estimating the lifetime distribution
  8. Proportional hazards models 
  9. Exposed to risk
  10. Graduation and statistical tests
  11. Methods of graduation
  12. Mortality projection
  13. Time Series
  14. Time Series
  15. Loss distributions
  16. Extreme value theory
  17. Copulas
  18. Reinsurance
  19. Risk models 1
  20. Risk models 2
  21. Machine learning

Actuarial Science CS2 Playlist

CS2

18,000.0022,000.00

CS2 Subject – Study Skills & Assessment

Technical skills

Subjects CS1 and CS2 are very mathematical and have relatively few questions requiring wordy

answers.

Exam skills

Exam question skill levels

In the CS subjects, the approximate split of assessment across the three skill types is:

  • Knowledge – 20%
  • Application – 65%
  • Higher Order skills – 15%.

Assessment

Assessment consists of:

  • Paper A – a 3¼-hour examination consisting of a number of questions of varying marks
  • Paper B – a 1¾-hour examination consisting of practical data analysis and statistical actuarial

modeling problems.

The online exams include an additional 5 minutes (ie 3 hours 20 minutes in total for Paper A and

For students to download and print the question paper, 1 hour and 50 minutes in total for Paper B).

In order to pass Subject CS2, both papers must be sat within the same examination sitting and a

combined mark of a pass achieved across the two papers.

Core study material

This section covers the function of the Syllabus, Core Reading, and ActEd text. It also explains how to apply this information efficiently in order to pass the exam.

Some of the information provided below can also be found in the introduction to the Core Reading.

The Core Reading supplements Syllabus material by ensuring that both depth and breadth are reinforced. As a result, it is critical that students have a solid understanding of the principles addressed by the Core Reading.

The examinations require students to demonstrate their understanding of the concepts described in the Core Reading and described in the Syllabus; this will be based on the legislation, professional guidance, and so on that are in effect when the Core Reading is published, i.e. on May 31 of the year preceding the examinations.
As a result, the April and September 2023 tests will be based on the Syllabus and Core Reading as of May 31, 2022. To prepare for the tests, we recommend that you always use the most recent Core Reading.

Examiners will use this Core Reading when preparing for exams. Students are urged to practice past examination questions and will benefit from additional tuition when preparing for exams. The Core Reading will be updated each year to reflect changes in the Syllabus and current practice and for clarity

Revision & Exam skills

Revision skills 

You will have taken numerous tests and will have mastered exam and revision procedures that are appropriate for you. However, due to the great volume of work involved in the Core Principles topics, it is not practical to leave all of your revisions until the last minute. Students who plan ahead of time have a better probability of passing their tests on the first try.

Unprepared students find themselves under time constraints during the exam. As a result, it is critical to identify techniques to maximize your score in the smallest amount of time. As soon as possible, rehearse a large number of exam-style questions under timed settings as part of your preparation. This will:

  • assist you in developing the necessary understanding of the procedures required 
  • highlight the major subjects that arise frequently in a variety of scenarios and questions
  • assist you in practicing the exact abilities required to pass the exam.

There are numerous resources for exam-style questions. former test papers, Practice problems at the end of each chapter (which include many former exam problems), assignments, mock examinations, Revision Notes, and ASET are all options.

Exam question skill levels  

Exam questions are not meant to be of the same difficulty, many skill levels for which questions can be set.

Any skill level is acceptable for questions:

  • Knowledge – demonstration of detailed knowledge and understanding of the topic
  •  Application – demonstration of an ability to apply the principles underlying the topic within a given context
  • Higher Order – demonstration of an ability to perform deeper analysis and assessment of situations, including forming judgments, taking into account different points of view, comparing and contrasting situations, suggesting possible solutions and actions, and making recommendations.

Frequently Asked Questions

What are the risk models in actuarial science?

In actuarial modelling, there are two primary types of models: deterministic models and stochastic models. Deterministic models are the more straightforward of the two. They both employ probabilistic estimates for each event and anticipate the number of events that will occur based on these estimations.

What is risk modeling and survival analysis?

The Risk Modelling and Survival Analysis Core Principles subject’s goal is to provide a foundation in mathematical and statistical modelling approaches relevant to actuarial work, such as stochastic processes and survival models and their applications.

How many hours do you need to study for CS2?

The fundamental subjects (CS1 and 2) 125 to 150 hours, depending on the course and the student’s previous educational background in the subject.

What is CS2 in actuarial science?

CS2 (Risk Modelling and Survival Analysis) builds on CS1. It enhances knowledge and abilities in risk modelling, time series analysis, stochastic processes (especially Markov chains and Markov jump processes), survival analysis (including regression methods for duration data), and graduation approaches.

What is CS2 Syllabus by IFOA?

  • Random variables and distributions for risk modelling (20%)
  • Time series (20%)
  • Stochastic processes (25%)
  • Survival models (25%)
  • Machine learning (10%)

In the CS subjects, the approximate split of assessment across the three skill
types is 20% Knowledge, 65% Application and 15% Higher Order skills.