Course in Individual vs Collective Risk Modelling
Online 300-hour course in individual vs collective risk modelling. 6 modules covering Directive 2009/138/EC (Solvency II), art. 101, Delegated Regulation (EU) 2015/35 and R (actuar). Assigned tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Distinguish between individual risk models and collective risk models.
Fit frequency distributions such as Poisson and negative binomial.
Fit light-tailed and heavy-tailed severity distributions.
Calculate aggregate loss using Panjer, FFT and simulation.
Incorporate dependence and heterogeneity between risks.
Estimate risk measures such as VaR and TVaR.
Apply the models to pricing, reserving and capital.
Who it's for
- Non-life actuary wishing to specialise in Individual vs Collective Risk Modelling.
- Quantitative risk analyst wishing to specialise in Individual vs Collective Risk Modelling.
- Capital modeller wishing to specialise in Individual vs Collective Risk Modelling.
- Reserving actuary wishing to specialise in Individual vs Collective Risk Modelling.
- Pricing actuary wishing to specialise in Individual vs Collective Risk Modelling.
- Actuarial consultant wishing to specialise in Individual vs Collective Risk Modelling.
- Graduates in engineering or sciences seeking to join insurance companies.
What you'll work with
- Directive 2009/138/EC (Solvency II), art. 101
- Delegated Regulation (EU) 2015/35
- IFRS 17
- ISAP 1 (International Standard of Actuarial Practice)
- Law 20/2015 (LOSSEAR)
- Royal Decree 1060/2015 (ROSSEAR)
6 modules · 300 h
1.1What question each model answers1.2Individual model: sum of risks per policy1.3Collective model: number of claims by amount1.4Independence assumptions and their limits1.5Choosing the framework according to line of business and available data1.6Exposure unit and observation period1.7Aggregate loss as a random variable1.8Moments of the aggregate loss1.9Practical advantages of each formulation1.10Workshop: the same portfolio modelled both ways
2.1Poisson and its central role in the collective model2.2Binomial and negative binomial2.3Poisson mixtures and portfolio heterogeneity2.4Compound Poisson processes2.5Maximum likelihood estimation2.6Goodness-of-fit testing2.7Overdispersion: diagnosis and treatment2.8Excess zeros in low-frequency portfolios2.9Time-dependent frequency2.10Practice: frequency fitting on real data
3.1Common families: exponential, gamma, lognormal and Pareto3.2Heavy tails and their effect on capital3.3Truncation by deductible and censoring by limit3.4Fitting with data modified by deductibles3.5Mixtures of distributions for atypical claims3.6Separation of peak claims and specific analysis3.7Claims inflation and revaluation3.8Graphical tests: QQ-plot and mean excess function3.9Model selection and information criteria3.10Practice: severity fitting with a deductible
4.1Convolution and transforms for aggregate loss4.2Panjer recursive algorithm4.3Normal and shifted gamma approximations4.4Monte Carlo simulation: design and number of replications4.5Variance reduction in simulation4.6Effect of deductibles, limits and coinsurance on the aggregate4.7Proportional and non-proportional reinsurance in the model4.8High percentiles and risk measures4.9Comparison of methods on the same case4.10Practice: aggregate distribution by Panjer and by simulation
5.1Why independence fails in practice5.2Common factors and systematic risk5.3Copulas: concept, basic families and prudent use5.4Tail dependence and its impact on capital5.5Credibility: combining individual and collective experience5.6Hierarchical models and random effects5.7Segmentation versus modelling heterogeneity5.8Geographical and event accumulations5.9Validation of dependence assumptions5.10Practice: effect of dependence at the 99.5th percentile
6.1From aggregate loss to risk premium6.2Safety loading and loading criteria6.3Reserves: provision for outstanding claims6.4Economic capital and solvency requirement6.5Stress tests and adverse scenarios6.6Actuarial documentation and independent review6.7Communicating uncertainty to management6.8Common mistakes when choosing a modelling framework6.9Tools and reproducibility of calculations6.10Final project: complete actuarial report for a portfolio
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is R (actuar), Python (SciPy), MATLAB, WTW Igloo, in free, academic or evaluation versions. The case studies work through real procedures for fitting distributions to portfolio data, the Panjer algorithm and Monte Carlo simulation, and calculation of aggregate loss quantiles. Assessment is continuous per module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Distinguish between individual risk models and collective risk models.
Fit frequency distributions such as Poisson and negative binomial.
Fit light-tailed and heavy-tailed severity distributions.
Calculate aggregate loss using Panjer, FFT and simulation.
Incorporate dependence and heterogeneity between risks.
Where this takes you
Requirements
- No prior degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow technical regulatory reading.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme is 300 hours in total, spread over 3 to 5 months. That is between 10 and 15 hours a week on average, compatible with a full-time job.
You work with R (actuar), Python (SciPy), MATLAB, WTW Igloo. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM Institute diploma upon passing the continuous assessment and the integrating project. It is in-house training, not an official qualification issued by the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are credited towards the higher programme. Check the credit transfer policy when you enrol.
Related programmes
Compliance in Mobility Contracts Course
Online 300-hour course in compliance in mobility contracts. 6 modules covering Royal Legislative Decree 1/2007 (General Consumer and User Protection Act), Law 7/1998 on General Terms…
Course in Security Auditing of Telematics Systems
Online 300-hour course in security auditing of telematics systems. 6 modules covering ISO/SAE 21434 (cybersecurity for road vehicles), UN Regulation No. 155 (cybersecurity) and Wireshark. Assigned…
Course in Solvency Assessment in Emerging Markets
Online 300-hour course in solvency assessment in emerging markets. 6 modules covering IAIS Insurance Core Principles (ICP), IAIS ComFrame and advanced Excel. Assigned tutor and open…
More in Insurance, Risk & Actuarial Data
All Insurance, Risk & Actuarial Data programmes → · How to apply · Fees & financing · Scholarships