Postgraduate Diploma in Residual Value Models for Vehicles
800-hour online Postgraduate Diploma in Residual Value Models for Vehicles. 8 modules covering IFRS 16 (leases), IFRS 9 (financial instruments, impairment) and Python (statsmodels, LightGBM). Personal tutor assigned and enrolment open.
Postgraduate Diploma in Residual Value Models for Vehicles — studying from Canada
Canada has a major insurance and financial services sector, with headquarters and operations concentrated in Toronto and Montréal. Insurers and reinsurers rely on actuarial science, risk modelling and data analytics for pricing, reserving and capital management. Federal and provincial regulators oversee solvency, conduct and consumer protection. Engineers and data specialists with risk and modelling skills find roles at insurers, brokers, consultancies and regulatory bodies.
Fees for Canada: C$1,700 (Canadian dollar), with instalments and employer sponsorship available.
Relevant bodies in Canada
Typical roles
Questions from Canada
Is this programme recognised by professional bodies in Canada for insurance and actuarial data work?
SEIUM's qualifications are private, not official state degrees, and are not accredited by a national body in Canada. Actuarial credentials in Canada are governed by the Canadian Institute of Actuaries, and actuarial practice is regulated under provincial and federal rules. A private engineering qualification does not confer these credentials, so confirm recognition with employers or the relevant body yourself.
How might this qualification be used by employers in Canada in insurance or risk roles?
Insurers, banks and risk teams in Canada may value engineering-based data analysis and risk modelling skills, but how they regard a private qualification is their decision. Hiring in these sectors often depends on experience, professional exams and specific credentials. Your final project can serve as evidence of applied skills, though it does not guarantee any role or salary outcome.
What are the practical demands of studying this online from Canada?
Study is fully online and in English, and no student visa is required if you study from home. Programme lengths range from 300 to 1,900 hours, so consider how many hours a week you can commit alongside work. You are assigned a technical tutor for support. Fees can be paid in instalments, and some students receive employer sponsorship, which is possible but not guaranteed.
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 role of residual value in car rental, leasing and financing products.
Identify the technical, commercial and regulatory factors that determine a vehicle's depreciation.
Build statistical models to forecast residual values by segment.
Apply machine learning algorithms to used vehicle transaction data.
Assess the particularities of electric vehicles, including battery degradation.
Measure and manage the residual risk of a contract portfolio.
Integrate residual value forecasts into lease pricing and financial reporting.
Who it's for
- Residual value analyst who wants to specialise in Residual Value Models for Vehicles.
- Asset risk manager in car rental who wants to specialise in Residual Value Models for Vehicles.
- Automotive leasing pricing manager who wants to specialise in Residual Value Models for Vehicles.
- Used vehicle remarketing analyst who wants to specialise in Residual Value Models for Vehicles.
- Mobility data scientist who wants to specialise in Residual Value Models for Vehicles.
- Automotive finance consultant who wants to specialise in Residual Value Models for Vehicles.
- Engineering or science graduates looking to enter vehicle rental and leasing.
What you'll work with
- IFRS 16 (leases)
- IFRS 9 (financial instruments, impairment)
- Regulation (EU) 2019/631 (CO2 emission standards for passenger cars)
- Regulation (EU) 2023/1542 (batteries and waste batteries)
- Regulation (EC) No 715/2007 (Euro 5 and Euro 6 type-approval)
- Regulation (EU) No 575/2013 (CRR) as regards residual risk
- Royal Decree 265/2021 (end-of-life vehicles)
8 modules · 800 h
1.1Concept of residual value and depreciation1.2Importance in rental, leasing and buy-back1.3Residual value risk for the lessor1.4Manufacturer buy-back guarantees1.5The used car market in Spain1.6Price cycles and supply of used vehicles1.7Price sources: Ganvam, Eurotax and portals1.8Mileage, condition and equipment1.9Effect of electrification on residual values1.10Case study: depreciation analysis of a model
2.1Make, model and segment2.2Age and mileage2.3Engine type and environmental label2.4Mechanical and cosmetic condition2.5Accident history2.6Equipment and options2.7Colour and market preferences2.8New launches and generation changes2.9Manufacturer discount policies2.10Practice: quantifying factors using advertisement data
3.1Exponential depreciation curves3.2Hedonic price regression3.3Generalised linear models of price3.4Cohort panel models3.5Quantile regression for risk3.6Time series of price indices3.7Validation and prediction error3.8Seasonal adjustment3.9Interpretation of coefficients3.10Laboratory: hedonic price model for used vehicles
4.1Legal web scraping and advertisement data4.2Cleaning and normalising model versions4.3Gradient boosting for price prediction4.4Neural networks and model embeddings4.5Auction and remarketing data4.6Telematics data on vehicle condition4.7Explainability of predictions4.8Continuous model updating4.9Error monitoring4.10Practice: residual value prediction with LightGBM
5.1Battery state of health (SoH)5.2Battery degradation and warranties5.3Technological obsolescence and range5.4Public incentives and their effect on prices5.5Charging infrastructure and demand5.6Second life and battery value5.7Battery passport under Regulation (EU) 2023/15425.8Residual risk in electrified portfolios5.9Regulatory scenarios for combustion engine bans5.10Case study: residual value of an electric SUV at 48 months
6.1Risk measurement and expected loss6.2Price stress scenarios6.3Accounting provisions for impairment6.4Coverage with guarantees and insurance6.5Residual value insurance and GAP6.6Portfolio diversification6.7Remarketing strategies6.8Setting rental instalments6.9Residual value committees6.10Workshop: stress test of a rental portfolio
7.1Offers with guaranteed future value7.2Consumer transparency7.3IFRS 16 and lessor accounting7.4Supervisory requirements on residual risk7.5Governance of valuation models7.6Interaction with credit risk7.7Forecasting remarketing results7.8Communication with dealers7.9Performance indicators7.10Practice: setting residual values for a commercial campaign
8.1Defining the vehicle segment8.2Collecting market data8.3Exploratory analysis8.4Building the model8.5Validation and backtesting8.6Stress scenarios8.7Proposal for a residual value table8.8Monitoring plan8.9Report and presentation8.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and a assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it possible to combine study with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (statsmodels, LightGBM), R (survival), JATO Dynamics, SAS Visual Analytics, advanced Excel, in free, academic or evaluation versions. Tests are studied using real procedures for depreciation curves by segment and engine type, backtesting of residual value forecasts, and battery health analysis for used electric vehicles. Assessment is continuous across each 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 role of residual value in car rental, leasing and financing products.
Identify the technical, commercial and regulatory factors that determine a vehicle's depreciation.
Build statistical models to forecast residual values by segment.
Apply machine learning algorithms to used vehicle transaction data.
Assess the particularities of electric vehicles, including battery degradation.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. A university degree is not 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 consists of 800 hours in total, spread over 6 to 8 months. That is between 10 and 15 hours a week on average, compatible with a full-time job.
You will work with Python (statsmodels, LightGBM), R (survival), JATO Dynamics, SAS Visual Analytics and advanced Excel. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An SEIUM own diploma upon passing the continuous assessment and the integrating project. It is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or diploma in the same area are credited towards the advanced programme. Check the credit transfer policy when you enrol.
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