CS2 – Risk Modelling and Survival Analysis
Develop Advanced Expertise in Statistical Risk Modelling, Stochastic Processes and Survival Analysis
CS2 – Risk Modelling and Survival Analysis is a Core Principles subject in the actuarial qualification pathway offered by the Institute and Faculty of Actuaries (IFoA), UK, and the Institute of Actuaries of India (IAI).
Building upon the statistical foundations developed in CS1, the subject introduces advanced mathematical and statistical techniques used to model uncertainty, analyse survival times, evaluate insurance risks and understand complex financial and insurance data.
CS2 combines risk modelling, time series analysis, stochastic processes, survival models and machine learning, developing the analytical and computational skills required for actuarial applications in life insurance, general insurance, pensions, healthcare and risk management.
Course Structure & Syllabus
CS2 combines advanced statistical theory with practical risk modelling and data analysis using R programming.
Key Topics Covered:
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Risk Models & Probability Distributions:
Individual and aggregate loss models, claim frequency and severity distributions, compound distributions, reinsurance arrangements and risk assessment.
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Extreme Value Theory & Dependence Modelling:
Extreme loss distributions, tail risk analysis, copulas, dependence structures and modelling relationships between financial and insurance risks.
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Time Series Analysis:
Stationary and non-stationary processes, autoregressive models, moving average models, ARMA, ARIMA, forecasting and financial time series applications.
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Stochastic Processes & Markov Models:
Markov chains, Markov jump processes, Poisson processes, transition probabilities, Kolmogorov equations and stochastic modelling.
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Survival Models & Statistical Estimation:
Survival functions, hazard rates, mortality analysis, censored data, Kaplan-Meier estimation, parametric survival models and regression techniques.
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Graduation & Mortality Modelling:
Graduation of mortality rates, smoothing techniques, experience analysis, statistical testing and applications to life insurance and pensions.
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Machine Learning & R Programming:
Classification and regression techniques, model evaluation, statistical simulations, predictive modelling and practical actuarial applications using R.
The CS2 syllabus focuses on statistical risk modelling, stochastic processes, survival analysis, forecasting and practical data analytics, developing essential skills for advanced actuarial and financial risk analysis.
Syllabus Topics & Weightages
The CS2 syllabus comprises five principal areas, with the following indicative weightages under the IFoA curriculum:
| Topic |
Weightage |
| Random Variables and Distributions for Risk Modelling |
20% |
| Time Series |
20% |
| Stochastic Processes |
25% |
| Survival Models |
25% |
| Machine Learning |
10% |
| Total |
100% |
These weightages indicate approximate syllabus coverage. Actual question distribution may vary between examination sittings.
Examination Structure
CS2 consists of two compulsory components: CS2A (Theory) and CS2B (Practical).
Both papers must be attempted during the same examination sitting.
| Particulars |
IAI (India) |
IFoA (UK) |
| Paper A – Theory |
Objective + Descriptive |
Descriptive |
| Paper A Duration |
3 Hours 15 Minutes |
3 Hours 20 Minutes |
| Paper A Weightage |
70% |
70% |
| Paper B – Practical |
R-Based |
R-Based |
| Paper B Duration |
1 Hour 45 Minutes |
1 Hour 50 Minutes |
| Paper B Weightage |
30% |
30% |
| Examination Mode |
Centre-Based Online |
In-Person at Exam Centres or Remotely Invigilated Online |
Important Examination Guidelines
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Paper A: Evaluates theoretical concepts, statistical calculations, stochastic models, survival analysis and actuarial problem-solving. IAI includes objective and descriptive questions, while IFoA follows a written-response format.
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Paper B: Tests practical statistical modelling, data analysis and risk assessment using R programming.
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Combined Assessment: Paper A contributes 70% and Paper B contributes 30% towards the final examination score.
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IFoA Examination Mode: Students can indicate their preference for an authorised examination centre or remote online invigilation. Final allocation is subject to availability and IFoA examination guidelines.
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IAI Examination Mode: Examinations are conducted online at designated examination centres in accordance with IAI’s examination arrangements.
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Examination Requirements: Students must comply with their respective institute’s guidelines regarding permitted calculators, actuarial tables, R software and examination conduct.
Passing Criteria
The passing requirements differ between IAI and IFoA.
| Institute |
Passing Requirements |
| IAI (India) |
Minimum 30% in each paper and 50% aggregate |
| IFoA (UK) |
Combined weighted marks must meet the pass mark determined for the examination sitting |
Important Information:
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Both Paper A and Paper B must be attempted during the same examination session.
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IAI requires candidates to meet both the individual paper minimum and the overall aggregate requirement.
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IFoA determines the passing mark for each examination sitting and does not prescribe a separate minimum passing mark for each paper.
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Candidates who do not clear CS2 must attempt both components again in a subsequent examination sitting.
Eligibility Criteria
CS2 is a Core Principles examination suitable for students developing advanced statistical and actuarial modelling skills.
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Students can pursue CS2 through the IAI or IFoA examination pathway, subject to the respective institute’s eligibility and registration requirements.
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A strong understanding of probability, statistics, mathematical modelling and statistical inference is recommended.
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Prior knowledge of CS1 is strongly recommended, as CS2 builds upon its statistical concepts.
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Under the IFoA pathway, students are not required to pass CS1 or another actuarial examination before attempting CS2.
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Familiarity with R programming is beneficial for the practical examination.
Learning Objectives
Studying CS2 develops the ability to:
- Analyse individual and aggregate insurance risks.
- Apply probability distributions and stochastic models.
- Understand and use Markov chains and stochastic processes.
- Develop time series models for forecasting.
- Analyse mortality, survival times and censored data.
- Apply graduation and survival modelling techniques.
- Understand extreme risk and dependence structures.
- Apply machine learning and statistical modelling using R.
Practical Applications of CS2
The knowledge gained in CS2 is applicable across several actuarial, financial and analytical disciplines:
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Life & Health Insurance: Mortality and morbidity modelling, survival analysis, critical illness modelling and health risk assessment.
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General Insurance: Claims frequency and severity analysis, aggregate loss modelling, reinsurance and extreme risk assessment.
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Pensions: Retirement modelling, life expectancy analysis and valuation of survival-related risks.
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Data Science & Healthcare Analytics: Survival analysis, predictive modelling, statistical forecasting and analysis of complex datasets.
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Enterprise Risk Management: Quantifying financial uncertainty, modelling extreme losses and assessing risk dependencies.
CS2 develops advanced statistical and modelling knowledge that supports applications across actuarial practice and provides a foundation for further subjects, including SP1, SP7, SP8 and SP9.
Technical Requirements – AEI Learning Application
To access online classes, recorded lectures and digital study resources, students must ensure their devices meet the following minimum technical requirements of the Actuators Educational Institute (AEI) Learning Application.
| Device / Platform |
Minimum Requirement |
| Android |
Android 9.0 or above |
| Windows PC / Laptop |
Windows 10 or above |
| iPhone / iPad (iOS) |
iOS 12.0 or above |
| MacBook / iMac (macOS) |
Apple M1 chip or above with macOS 14 or later |