Postgraduate Diploma in Revenue Management Applied to the Insurance Sector
Online postgraduate diploma of 800 hours in revenue management applied to the insurance sector, structured in 8 modules covering customer analytics, demand elasticity, price optimisation, distribution channels, retention and portfolio value, and regulation, ethics and technology, with an assigned technical tutor.
Postgraduate Diploma in Revenue Management Applied to the Insurance Sector — 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$1,840 (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
Adapt the principles of revenue management to the nature of insurance.
Segment customers using value and behaviour analytics.
Estimate demand elasticity at new business and renewal.
Optimise prices under technical, commercial and regulatory constraints.
Manage profitability by distribution channel.
Design retention strategies based on customer lifetime value.
Assess the ethical and regulatory limits of differential pricing.
Who it's for
- Insurance revenue managers.
- Pricing and elasticity analysts.
- Customer retention managers.
- Distribution channel managers.
- Commercial data scientists.
- Pricing strategy consultants.
- Engineering or science graduates looking to join a non-life insurer.
What you'll work with
- Directive (EU) 2016/97 (IDD) (product oversight and governance)
- EIOPA supervisory statement on differential pricing practices (2023) (fair pricing supervision)
- Directive 2005/29/EC (unfair commercial practices)
- Directive (EU) 2019/2161 (modernisation of consumer protection)
- Regulation (EU) 2016/679 (GDPR) (data protection)
- Ley 50/1980 (Spanish Insurance Contract Act)
- Earnix
- Python (PuLP, scikit-learn)
- Gurobi
- Tableau
- SAS Customer Intelligence
8 modules
1.1Origins in airlines and hotels1.2Adaptation to the insurance sector1.3Differences between RM and actuarial pricing1.4Customer lifetime value1.5Customer and channel segmentation1.6Policy life cycle1.7Indicators: written premium, retention and margin1.8Organisation and roles of the RM function1.9Regulatory and reputational risks1.10Case study: RM diagnosis of a motor insurer
2.1Purchase propensity models2.2Lapse and churn models2.3Actuarial customer lifetime value2.4Segmentation with clustering2.5Cohort analysis2.6Digital interaction data2.7Attribution of acquisition channels2.8Customer data quality and governance2.9Visualisation for decision-making2.10Laboratory: CLV model for a home insurance portfolio
3.1Demand theory and elasticity3.2Estimation with quote data3.3Logistic conversion models3.4Effect of competition and price comparison sites3.5Renewal elasticity3.6Heterogeneity across segments3.7Design of price experiments3.8Endogeneity and estimation bias3.9Causal and uplift models3.10Practical exercise: estimating elasticities by segment
4.1Objective function: volume, premium and profit4.2Business and regulatory constraints4.3Non-linear programming and heuristics4.4Portfolio efficient frontier4.5Individual and segment-level optimisation4.6Scenarios and sensitivity analysis4.7Ban on price walking4.8Fair price and customer value4.9Approval and change control4.10Workshop: constrained renewal optimisation
5.1Pricing by channel: direct, agents and bancassurance5.2Commissions and acquisition cost5.3Price comparison sites and aggregators5.4Bundling and cross-selling5.5Commercial discounts and their control5.6Campaigns and promotions5.7Underwriting capacity management5.8Customer experience and perceived price5.9Commercial indicators by channel5.10Case study: pricing strategy on a comparison site
6.1Proactive retention strategies6.2Next-best-action models6.3Personalised retention offers6.4Managing counter-offers6.5Portfolio value and profitable growth6.6Impact on the combined ratio6.7Reinsurance and risk appetite6.8Premium and claims forecasting6.9Revenue management in life insurance6.10Practical exercise: CLV-based retention campaign
7.1Product oversight and governance (POG)7.2Fair treatment of customers and Consumer Duty7.3EIOPA guidance on pricing practices7.4GDPR and profiling7.5EU AI Act7.6Real-time decision platforms7.7Automation and monitoring7.8Pricing model governance7.9Audit of results7.10Case study: review of a differential pricing practice
8.1Portfolio diagnosis8.2Customer segmentation8.3Demand and retention models8.4Optimisation strategy8.5Simulation of results8.6Regulatory analysis8.7Implementation plan8.8Monitoring dashboard8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
The programme is delivered 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Earnix, Python (PuLP, scikit-learn), Gurobi, Tableau and SAS Customer Intelligence, in free, academic or evaluation versions. Practical work is based on real procedures: estimating renewal elasticity, price optimisation with business constraints and A/B experiments in the digital channel. Assessment is continuous by module, plus the final project.
Standards covered: Directive (EU) 2016/97 (IDD); EIOPA supervisory statement on differential pricing practices (2023); Directive 2005/29/EC; Directive (EU) 2019/2161; Regulation (EU) 2016/679 (GDPR); Ley 50/1980.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- An internet connection and a computer able to run the programme software.
- English sufficient to read technical standards.
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 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Earnix, Python (PuLP, scikit-learn), Gurobi, Tableau and SAS Customer Intelligence, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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