Actuarial Science CS2 An Introductory Brief

Get ready to summon yourself to some insane statistics and modeling techniques! This paper will be a delight to those having a statistics background. Actuarial Science CS2: Risk Modelling and Survival Analysis builds on the knowledge of CS1: Actuarial Statistics. Prerequisite of CS1 is vital for CS2.

CT4 and CT6 are clubbed together to form CS2 under new curriculum 2019. CS2 builds up your knowledge to use techniques to model risk using statistical distributions, describe and use methods to analyze time series models, stochastic processes (majorly Markov chains and Markov jump processes), techniques of survival analysis and graduation methods.

This paper also introduces you to the high-level machine learning additional to the theory and application of concepts covered in this paper using R programming.

CS2 is further divided into two parts, i.e. CS2A and CS2B. CS2A will be a 3 hours 15 minutes theoretical exam sustaining 70% weight of CS2 and CS2B will be a 1 hour 45 minutes practical exam using R programming fetching 30% weight of the whole paper respectively. The outcome will be a single mark.

It isn’t obligatory to pass both CS1A and CS2B individually, marks of both the exams will be added together, given you achieved the pass mark, you will pass. But, it is mandatory to sit for both the exams in the same session.

Links To Other Actuarial Papers

  • The material in this paper is applied to actuarial modeling in Actuarial Mathematics (i.e. CM1 and CM2).
  • Topics discussed in this paper are further tuned in SP1 – Health and Care Principles, SP7 – General Insurance Reserving and Capital Modelling Principles, SP8 – General Insurance Pricing Principles and SP9 – Enterprise Risk Management Principles.

Weight Of Topics

In Actuarial Statistics subjects, the division of the assessment across the three skill levels is approximately 20% Knowledge, 65% Application and 15% Higher order skills.

The course is vast as well as conceptual and applicative at the same time. To help you understand the content better, I’ll be explaining you the objectives of the paper topic wise.

So, without further ado, let’s unravel the CS2 coursework:


  • Loss distributions, with and without risk sharing
  • Compound distributions and their applications in risk modeling
  • Introduction to copulas
  • Introduction to extreme value theory


  • Introduction to types and general properties of the time series
  • Concepts underlying time series models
  • Applications of time series models


  • Describe and classify stochastic processes
  • Define and apply a Markov chain
  • State the essential features and derive Chapman-Kolmogorov equations that represent a Markov chain
  • Define and apply a Markov process
  • State the essential features and derive Chapman-Kolmogorov equations that represent a Markov process
  • Describe and differentiate between multiple state model and multiple decrement model


  • Explain the concept of survival models
  • Describe estimation procedures for lifetime distributions
  • Derive maximum likelihood estimators for transition intensities
  • Estimate transition intensities dependent on age (exact or census)
  • Graduation and graduation tests
  • Mortality projection


  • Explain and discuss the main branches of machine learning
  • Explain and apply high-level concepts relevant to learning from data
  • Describe and give examples of key supervised and unsupervised machine learning techniques
  • Explain in detail and use appropriate software to apply machine learning techniques

The practical exam CS2B will be done in R on real data sets based on the data analysis and statistical modeling discussed in CS2A course material.


  • For this paper specifically, surrender yourself to the study material. I have seen many a time that students who are fully prepared and have done ten-years are unable to clear the exam (especially CT4 under old curriculum) because they aren’t thorough with the concepts and haven’t gone through the study material even once.
  • For statistics-based papers, remember the golden rule: Emphasize more on the concept that doing questions. You can have an infinite variety of questions, but if you know the concept well, no matter how much twisted the question comes in the pen-paper based or practical exam, you would be able to solve it correctly.
  • Prepare and practice material simultaneously on pen-paper as well as on R. Do make your own notes and re-read them again and again.
  • Be efficient– make your own study plan and stick to it. The new course is really good and enough to make you industry ready as a fresher. Don’t just aim to clear this exam rather understand and absorb the knowledge learned through this paper.
  • Also do Question-Banks given in the core reading, since there are no past year papers of CS2 yet, you can practice specimen exam papers given on the IFOA website.

So, this is all from my side! I hope I was able to brief you CS2 in the best possible way. 


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