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Master’s in Credit, Leasing and Residual Value in Mobility Engineering

Online master's programme of 1,900 hours in credit, leasing and residual value engineering in mobility, structured in 12 modules covering mobility finance, regulation and accounting, credit risk, expected loss, residual value, electric vehicle residual risk, renting, remarketing and portfolio management, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Compare mobility finance products.

02

Apply credit regulation and accounting standards.

03

Build credit risk models.

04

Calculate expected loss and provisions.

05

Model vehicle residual values.

06

Manage the residual risk of electric vehicles.

07

Optimise portfolios, renting and remarketing.

Profile

Who it's for

  • Credit risk analysts.
  • Residual value managers.
  • Renting product managers.
  • Remarketing analysts.
  • Finance portfolio managers.
  • Financial data scientists.
  • Engineering or science graduates seeking to join captive finance companies.
Standards & tools

What you'll work with

  • Law 16/2011 (Spanish consumer credit contracts)
  • Directive (EU) 2023/2225 (consumer credit agreements)
  • Law 28/1998 (Spanish instalment sale of movable goods)
  • IFRS 9 (financial instruments)
  • IFRS 16 (leases)
  • Regulation (EU) 575/2013 (prudential requirements)
  • Bank of Spain Circular 4/2017 (financial reporting rules for credit institutions)
  • Regulation (EU) 2020/852 (EU taxonomy)
  • R
  • Python with scikit-learn
  • SAS
  • Microsoft Power BI
Syllabus

12 modules · 1900 h

  1. 1.1Vehicle finance market
  2. 1.2Consumer loans for vehicles
  3. 1.3Finance leasing
  4. 1.4Long-term renting
  5. 1.5Vehicle subscription
  6. 1.6Corporate fleet finance
  7. 1.7Finance for machinery and industrial vehicles
  8. 1.8Captive finance companies
  9. 1.9Business risks
  10. 1.10Case study: comparison of finance products
  1. 2.1Consumer Credit Contracts Act
  2. 2.2New EU Consumer Credit Directive
  3. 2.3Instalment Sale of Movable Goods Act
  4. 2.4Bank of Spain accounting rules
  5. 2.5IFRS 9 financial instruments
  6. 2.6IFRS 16 leases
  7. 2.7Bank capital requirements
  8. 2.8Financial consumer protection
  9. 2.9Anti-money laundering
  10. 2.10Laboratory: accounting treatment of a renting contract
  1. 3.1Customer creditworthiness analysis
  2. 3.2Credit scoring models
  3. 3.3Logistic regression in scoring
  4. 3.4Machine learning in credit risk
  5. 3.5Probability of default
  6. 3.6Loss given default
  7. 3.7Exposure at default
  8. 3.8Validation of risk models
  9. 3.9Fairness in credit decisions
  10. 3.10Practical exercise: scoring model for vehicle finance
  1. 4.1IFRS 9 expected loss model
  2. 4.2Impairment stages
  3. 4.3Significant increase in credit risk
  4. 4.4Forward-looking macroeconomic scenarios
  5. 4.5Loan loss provisions
  6. 4.6Collections and arrears management
  7. 4.7Vehicle repossession
  8. 4.8Vintage analysis
  9. 4.9Reporting to supervisors
  10. 4.10Laboratory: expected loss calculation for a portfolio
  1. 5.1The concept of residual value
  2. 5.2Factors that determine residual value
  3. 5.3Depreciation by age and mileage
  4. 5.4Used-car market data
  5. 5.5Statistical residual value models
  6. 5.6Machine learning models
  7. 5.7Scenarios and sensitivity
  8. 5.8Setting the residual in contracts
  9. 5.9Residual risk governance
  10. 5.10Practical exercise: residual value model for an SUV
  1. 6.1Uncertainty in the used EV market
  2. 6.2Battery state of health and its measurement
  3. 6.3Battery warranties
  4. 6.4Technological obsolescence of the vehicle
  5. 6.5Effect of public incentives
  6. 6.6New vehicle prices
  7. 6.7Charging infrastructure and demand
  8. 6.8Mitigation strategies
  9. 6.9Experience of finance companies
  10. 6.10Case study: four-year residual of an electric vehicle
  1. 7.1Components of the renting fee
  2. 7.2Maintenance included in the fee
  3. 7.3Insurance included in renting
  4. 7.4Tyre management and assistance
  5. 7.5Excess mileage charges
  6. 7.6Damage on return
  7. 7.7Total cost of ownership for the customer
  8. 7.8Taxation of renting
  9. 7.9Business indicators
  10. 7.10Practical exercise: calculating a renting fee
  1. 8.1Used vehicle sales channels
  2. 8.2Professional vehicle auctions
  3. 8.3Sales to private buyers
  4. 8.4Vehicle reconditioning
  5. 8.5Inspection on return
  6. 8.6Remarketing prices
  7. 8.7Export of used vehicles
  8. 8.8Sales lead times and costs
  9. 8.9Remarketing indicators
  10. 8.10Case study: remarketing strategy for a fleet
  1. 9.1Portfolio composition
  2. 9.2Concentrations by make and model
  3. 9.3Combined risk management
  4. 9.4Residual risk hedging
  5. 9.5Residual value insurance
  6. 9.6Portfolio securitisation
  7. 9.7Funding of the entity
  8. 9.8Stress testing
  9. 9.9Portfolio reporting
  10. 9.10Practical exercise: stress test of a renting portfolio
  1. 10.1Digital origination of deals
  2. 10.2Identity verification
  3. 10.3Connected vehicle data
  4. 10.4Used-car pricing platforms
  5. 10.5Decision automation
  6. 10.6Artificial intelligence in finance
  7. 10.7Data protection
  8. 10.8Cybersecurity in financial services
  9. 10.9Customer experience
  10. 10.10Laboratory: digital origination flow
  1. 11.1Green vehicle finance
  2. 11.2EU taxonomy in finance
  3. 11.3Climate risks in portfolios
  4. 11.4Circular economy of the vehicle
  5. 11.5Second life of batteries
  6. 11.6Subscription models
  7. 11.7Mobility as a Service
  8. 11.8Partnerships with manufacturers
  9. 11.9Market trends
  10. 11.10Case study: subscription product for electric vehicles
  1. 12.1Selection of the product or portfolio
  2. 12.2Regulatory analysis of the product
  3. 12.3Credit risk model
  4. 12.4Residual value model
  5. 12.5Fee calculation
  6. 12.6Portfolio analysis
  7. 12.7Remarketing plan
  8. 12.8Profitability analysis
  9. 12.9Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

100% online training 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 the intake, so the programme can be combined with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is R, Python with scikit-learn, SAS and Microsoft Power BI, in free, academic or evaluation versions. Testing is studied through real procedures for credit scoring models, residual value forecasting and renting fee calculation. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: Law 16/2011, Directive (EU) 2023/2225, Law 28/1998, IFRS 9, IFRS 16, Regulation (EU) 575/2013, Bank of Spain Circular 4/2017, Regulation (EU) 2020/852.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of Law 16/2011, Directive (EU) 2023/2225 and Law 28/1998 applied to real cases, not as a theoretical annex.
Industry software:R, Python with scikit-learn, SAS and Microsoft Power BI, in free, academic or evaluation versions.
Master's Thesis with defence:a complete mobility finance product or portfolio, with regulatory analysis, credit risk and residual value models, fee calculation, remarketing plan and profitability analysis, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Product and regulatory analysis
Compare finance products and determine the accounting treatment of a renting contract.
Credit risk and expected loss
Build a vehicle finance scoring model and calculate the portfolio's expected loss.
Residual value modelling
Model the residual value of an SUV and of an electric vehicle at four years.
Renting and portfolio
Calculate a renting fee and stress-test a renting portfolio.
Master's Thesis
Design and assess a complete mobility finance product or portfolio, defended before a panel.
Career opportunities

Where this takes you

Credit risk analystResidual value managerRenting product managerRemarketing analystFinance portfolio managerFinancial data scientist
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • Internet connection and a computer capable of running the programme's 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.

Apply now Scholarships
FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with R, Python with scikit-learn, SAS and Microsoft Power BI, 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 Master's Thesis. 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 in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A university degree in engineering, science or architecture (or equivalent professional experience), 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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