Course in Actuarial Scenario Simulation
Online 300-hour course in actuarial scenario simulation. 6 modules covering Directiva 2009/138/CE (Solvency II, art. 45 ORSA), Delegated Regulation (EU) 2015/35 and Moody’s Scenario Generator. Assigned tutor and open enrolment.
Course in Actuarial Scenario Simulation — studying from Singapore
Singapore is a major insurance and reinsurance hub in Asia, regulated by the Monetary Authority of Singapore. Engineering skills support risk modelling, catastrophe analysis, data analytics and actuarial work for insurers and reinsurers. The sector draws on data science and quantitative methods, with demand from insurers, brokers and risk consultancies. The city's financial ecosystem makes it a common base for global risk and actuarial teams.
Fees for Singapore: S$639 (Singapore dollar), with instalments and employer sponsorship available.
Relevant bodies in Singapore
Typical roles
Questions from Singapore
Will this qualification be recognised by professional bodies in Singapore?
SEIUM's qualifications are private, not official state degrees, and are not accredited by any national body. In Singapore, actuarial work is linked to the Singapore Actuarial Society, and insurance is regulated by the Monetary Authority of Singapore. Recognition of a private qualification is decided by employers or the relevant body, so confirm with them directly before you enrol.
How might this training be used by employers in Singapore?
Singapore's insurance, banking and risk functions employ people with analytical and data skills. An engineering-based risk and data programme may complement such roles, but it does not guarantee a position or a specific career outcome. Employers usually weigh professional exams, experience and demonstrated analytical ability, so your final project and work history will matter as much as the qualification title.
Can I study this alongside a full-time job, and can my employer help fund it?
Because the course is fully online and taught in English, you can study from Singapore without travelling, and no student visa is needed for online study. The workload is substantial, so plan carefully around your job. Fees can be paid in instalments, and employer sponsorship is possible; many Singapore companies support job-relevant study, so discuss it with your manager.
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
Explain the use of scenarios in planning and risk management.
Select relevant scenarios according to the entity's risk profile.
Build coherent economic and market scenarios.
Design technical, catastrophe and climate scenarios.
Project the balance sheet and capital under each scenario.
Interpret the results and propose management actions.
Integrate scenario analysis into the ORSA process.
Who it's for
- Risk management actuary who wants to specialise in Actuarial Scenario Simulation.
- Scenario and stress testing analyst who wants to specialise in Actuarial Scenario Simulation.
- ORSA manager who wants to specialise in Actuarial Scenario Simulation.
- Life modelling actuary who wants to specialise in Actuarial Scenario Simulation.
- Climate risk analyst who wants to specialise in Actuarial Scenario Simulation.
- Actuarial consultant who wants to specialise in Actuarial Scenario Simulation.
- Graduates in engineering or science seeking to join insurance companies.
What you'll work with
- Directiva 2009/138/CE (Solvencia II, art. 45 ORSA)
- Reglamento Delegado (UE) 2015/35
- EIOPA Guidelines on the own risk and solvency assessment (ORSA)
- EIOPA Opinion on climate change scenarios in the ORSA (2021)
- IFRS 17 (insurance contracts)
- ASOP No. 56 (modelling)
- TCFD Recommendations
6 modules · 300 h
1.1Deterministic, stress and reverse scenarios1.2Difference between a scenario and a probability distribution1.3Regulatory scenarios versus own scenarios1.4Link with the business plan and risk appetite1.5Time horizon and scenario granularity1.6Scenario narrative: cause, chain and effect1.7Plausibility and severity: how they are calibrated1.8Business involvement in design1.9Minimum documentation of a scenario1.10Workshop: building the narrative of an adverse scenario
2.1Relevant macro variables: interest rates, inflation, unemployment and growth2.2Economic scenario generators and their calibration2.3Scenarios of sudden rises and falls in interest rates2.4Equity market falls and widening spreads2.5Inflationary scenario and its effect on claims2.6Liquidity crisis and forced asset sales2.7Internal consistency between scenario variables2.8Using historical episodes as templates2.9Translating the scenario into balance sheet impact2.10Practice: impact of an interest rate scenario on own funds
3.1Peak and accumulation claims scenario3.2Natural catastrophe: footprint, exposure and loss3.3Pandemic and mortality and morbidity scenarios3.4Reinsurance failure and counterparty default scenario3.5Claims deterioration from cost inflation3.6Scenario of rising litigation3.7Severe technological and operational failure3.8Combined scenarios and correlation between events3.9Exhaustion of reinsurance layers3.10Practice: catastrophe scenario on a real portfolio
4.1Acute and chronic physical risk4.2Warming scenarios and their assumptions4.3Transition risk: regulation, technology and demand4.4Long horizon and discounting of distant impacts4.5Climate exposure of assets and liabilities4.6Effect on the insurability of certain areas4.7Reinsurance and capacity withdrawal scenarios4.8Data and sources for climate scenarios4.9Supervisory expectations on climate matters4.10Practice: recurrent flood scenario in an area
5.1Balance sheet and technical account projection model5.2New business and management assumptions5.3Management actions and their credibility5.4Calculation of the solvency ratio under scenario5.5Reverse scenario: how far can one go5.6Sensitivity analysis versus scenario analysis5.7Comparison between scenarios and risk hierarchy5.8Presenting results on one page5.9Common pitfalls when interpreting a scenario5.10Practice: comparison table of five scenarios
6.1Fit of scenarios within the risk and solvency self-assessment6.2Board approval and the role of key functions6.3Associated contingency and recovery plans6.4Annual review of the scenario set6.5Independent validation of the process6.6Required documentation and audit trails6.7Communication to the supervisor and the market6.8Use of scenarios in real decisions6.9Common errors in stress exercises6.10Final project: scenario set and its report
How you'll learn
Fully 100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the course with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Moody’s Scenario Generator, R, Python (NumPy, pandas), FIS Prophet, advanced Excel, in free, academic or evaluation versions. The case studies cover real procedures for generating stochastic economic scenarios, balance sheet projection under NGFS climate scenarios and ORSA exercises with adverse scenarios. Assessment is continuous by 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.
Explain the use of scenarios in planning and risk management.
Select relevant scenarios according to the entity's risk profile.
Build coherent economic and market scenarios.
Design technical, catastrophe and climate scenarios.
Project the balance sheet and capital under each scenario.
Where this takes you
Requirements
- No prior qualification is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow technical regulatory texts.
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 totals 300 hours, 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 Moody’s Scenario Generator, R, Python (NumPy, pandas), FIS Prophet, advanced Excel. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM own diploma upon passing the continuous assessment and the integrating project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the advanced programme. Check the recognition policy when you enrol.
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