Course in Actuarial Pricing Model Validation
Online 300-hour course in actuarial pricing model validation. 6 modules with ASOP No. 56 (modelling), ASOP No. 12 (risk classification) and R. Assigned tutor and open enrolment.
Course in Actuarial Pricing Model Validation — studying from India
India's insurance market is expanding, with life and general insurers, reinsurers and technology providers based in Mumbai, Delhi NCR, Chennai and Hyderabad. The Insurance Regulatory and Development Authority of India regulates the sector, and the Life Insurance Corporation of India and General Insurance Corporation of India are prominent public players. Insurers increasingly use data analytics, telematics and risk modelling, creating demand for actuarial and data professionals. Engineers and analysts in this area build pricing models, underwriting tools and risk assessment platforms for motor, property and health insurance.
Fees for India: ₹84,500 (Indian Rupee), with instalments and employer sponsorship available.
Relevant bodies in India
Typical roles
Questions from India
Is there a recognised actuarial or risk professional body in India for this area?
The main professional body for actuaries in India is the Institute of Actuaries of India (IAI), and insurers are regulated by IRDAI. SEIUM's qualifications are private and not accredited by any national body, so they do not give you IAI membership or any official status. Check the IAI's own exam and membership requirements before deciding.
Which employers in India hire for insurance, risk and actuarial data roles?
Life and general insurers, reinsurers, banks, consultancies and risk analytics teams hire for data and risk roles. Employers set their own hiring standards and decide how much weight to give a private qualification. Practical experience with data and modelling usually matters a great deal, so the course is best viewed as one part of your profile.
How is the programme delivered and how is it paid for in India?
The programme is delivered entirely online in English, so you can study from home with no student visa needed. Each student has an assigned technical tutor and completes a final project. Fees are payable in instalments, and employer sponsorship is possible, which many working professionals use to manage cost alongside their job.
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 purpose of pricing model validation and its audiences.
Validate the quality of the data and the model assumptions.
Apply technical tests of fit, discrimination and stability.
Verify the correct implementation of the model in production.
Assess the fairness and explainability of the resulting prices.
Write a validation report with findings and recommendations.
Design a model risk governance framework.
Who it's for
- Actuarial model validator wishing to specialise in Actuarial Pricing Model Validation.
- Pricing actuary wishing to specialise in Actuarial Pricing Model Validation.
- Model risk manager wishing to specialise in Actuarial Pricing Model Validation.
- Insurance data scientist wishing to specialise in Actuarial Pricing Model Validation.
- Internal model auditor wishing to specialise in Actuarial Pricing Model Validation.
- Actuarial consultant wishing to specialise in Actuarial Pricing Model Validation.
- Graduates in engineering or sciences seeking to enter insurance companies.
What you'll work with
- ASOP No. 56 (modelling)
- ASOP No. 12 (risk classification)
- ASOP No. 23 (data quality)
- SR 11-7 (guidance on model risk management)
- Regulation (EU) 2024/1689 (Artificial Intelligence Act)
- Commission Delegated Regulation (EU) 2017/2358 (insurance product governance)
- ISO/IEC 23894 (artificial intelligence risk management)
6 modules · 300 h
1.1Independent validation versus developer self-review1.2Validation across the model lifecycle1.3Expectations of the supervisor and the actuarial function1.4Scope of validation: data, method, implementation and use1.5Levels of validation according to model criticality1.6Model inventory and its classification1.7The role of internal audit1.8The validator's genuine independence1.9Minimum documentation the validator should receive1.10Workshop: defining the scope of a validation
2.1Data traceability from source2.2Representativeness of the experience period2.3Quality controls and reconciliation with accounting2.4Treatment of large losses and catastrophes2.5Trend, inflation and development assumptions2.6Exclusions and filters applied and their justification2.7Data leakage in the training set2.8Prohibited variables and indirect proxies2.9Documentation of applied expert judgement2.10Practice: critical review of a model's database
3.1Suitability of the method to the problem3.2Goodness of fit and residual analysis3.3Out-of-sample and out-of-period validation3.4Calibration: predicted versus observed by decile3.5Discriminatory power and its metrics3.6Stability of coefficients and factors3.7Sensitivity analysis to key assumptions3.8Comparison with alternative and benchmark models3.9Model stress testing3.10Practice: test battery on a tariff model
4.1Verification of implementation in the rating engine4.2Recalculation and premium reconciliation tests4.3Version control and environments4.4Handling edge cases and out-of-range values4.5Drift monitoring and alerts4.6Effective use of the model in decisions4.7Manual overrides and their control4.8Functional documentation for the business4.9Contingency plan for model failure4.10Practice: implementation test plan
5.1Impact analysis by customer groups5.2Fairness metrics and their limitations5.3Global and local model explainability5.4Automated decisions and human intervention5.5European artificial intelligence regulation applied to pricing5.6Transparency towards the customer and the supervisor5.7Reputational risk of the model5.8Decision logging and audit trails5.9Interaction with data protection5.10Practice: fairness report on a pricing model
6.1Structure of the validation report6.2Classification of findings by severity6.3Recommendations and remediation plan6.4Tracking of open findings6.5Communication with the development team6.6Presentation to the model committee and the board6.7Periodic validation and review triggers6.8Quality metrics for the validation process itself6.9Common errors in validation reports6.10Final project: complete validation report on a pricing model
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and assigned technical tutor. No fixed schedules: the student advances at his own pace within the call, which allows him to make it compatible with the work.
Each module combines theory, guided reading of the original norm and applied exercises. The work software is R, Python (SciKit-Learn, SHAP), WTW Emblem, Akur8, SAS, in free, academic or evaluation versions. The trials are studied on actual cross-validation and backtesting of GLM models, stability analysis and variable drift, equity tests and explainability of a price model. The evaluation is continuous by module plus the final integrator project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Explain the purpose of pricing model validation and its audiences.
Validate the quality of the data and the model assumptions.
Apply technical tests of fit, discrimination and stability.
Verify the correct implementation of the model in production.
Assess the fairness and explainability of the resulting prices.
Where this takes you
Requirements
- No prior degree required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of 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 an average of 10 to 15 hours per week, compatible with a full-time job.
The course uses R, Python (scikit-learn, SHAP), WTW Emblem, Akur8, SAS. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An SEIUM own diploma on 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 credited towards the advanced programme. Check the credit transfer policy when you enrol.
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