Postgraduate DiplomaInsurance, Risk & Actuarial Data Applications open

Postgraduate Diploma in Credit Risk in Automotive Leasing

Online 800-hour Postgraduate Diploma in Credit Risk in Automotive Leasing. 8 modules covering Regulation (EU) 575/2013 (CRR), IFRS 9 (expected credit loss) and SAS Credit Scoring. Dedicated tutor and enrolment open.

Duration800 h
ModeOnline
AwardSEIUM Institute diploma

Postgraduate Diploma in Credit Risk in Automotive Leasing — studying from the United Kingdom

Insurance and risk analysis are important sectors in the United Kingdom, with London's market, the City of London and Edinburgh's financial services hub employing large numbers of actuaries, risk analysts and data specialists. Engineering knowledge is increasingly valuable in assessing risk for vehicles, infrastructure, energy and emerging technologies. Insurers and reinsurers use modelling, catastrophe analysis and telematics data. Regulation by the Prudential Regulation Authority and the Financial Conduct Authority shapes professional practice in this area.

Fees for the United Kingdom: £746 (Pound sterling), with instalments and employer sponsorship available.

Relevant bodies in the United Kingdom

  • Institute and Faculty of Actuaries (IFoA)
  • Prudential Regulation Authority (PRA)
  • Financial Conduct Authority (FCA)
  • Lloyd's of London

Typical roles

  • Actuarial Analyst
  • Risk Engineer
  • Insurance Data Analyst
  • Catastrophe Modelling Analyst

Questions from the United Kingdom

Which UK bodies relate to actuarial and risk qualifications, and does SEIUM's training count towards their exams?

In the UK, actuarial professional status is governed by the Institute and Faculty of Actuaries, which runs its own examinations and accreditation. SEIUM's training is not accredited by the IFoA or any national body, and it does not confer exemptions from those exams unless the IFoA itself decides so. Confirm exemption policies directly with the IFoA before enrolling.

Do UK insurers and risk firms hire people with private online engineering or data qualifications?

UK insurers and risk consultancies recruit on the basis of skills, experience and recognised credentials. A private qualification may support an application where it demonstrates applied data or risk modelling, but employers decide its value case by case. Practical project work often carries more weight, so present your final project clearly on your CV and in interviews.

How much study time is needed, and can I pay for it in instalments while working in the UK?

Programmes range from 300 hours for specialist courses to 1,900 hours for master's programmes, all delivered online in English. You are assigned a technical tutor for support. Fees are payable in instalments, and employer sponsorship is possible. Plan weekly study hours realistically, as the total hours are substantial for a part-time learner.

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Learning outcomes

What you will be able to do

01

Describe leasing and renting products and their risk profile.

02

Explain the fundamentals of credit risk and its measurement.

03

Develop applicant admission and scoring models.

04

Estimate PD, LGD and EAD parameters for automotive portfolios.

05

Calculate expected credit loss provisions in accordance with IFRS 9.

06

Design monitoring strategies, early warning systems and debt recovery.

07

Manage the portfolio considering emerging risks such as the residual value of electric vehicles.

Profile

Who it's for

  • Credit risk analyst who wants to specialise in Credit Risk in Automotive Leasing.
  • Scoring modeller who wants to specialise in Credit Risk in Automotive Leasing.
  • Transaction admissions manager who wants to specialise in Credit Risk in Automotive Leasing.
  • Recovery manager who wants to specialise in Credit Risk in Automotive Leasing.
  • IFRS 9 provisions analyst who wants to specialise in Credit Risk in Automotive Leasing.
  • Risk model validator who wants to specialise in Credit Risk in Automotive Leasing.
  • Graduates in engineering or sciences seeking to join captive finance companies.
Standards & tools

What you'll work with

  • Regulation (EU) 575/2013 (CRR)
  • IFRS 9 (expected credit loss)
  • EBA/GL/2020/06 Guidelines on loan origination and monitoring
  • IFRS 16 (leases)
  • Bank of Spain Circular 4/2017
  • Directive (EU) 2023/2225 (consumer credit agreements)
  • Directive 2013/36/EU (CRD)
Syllabus

8 modules · 800 h

  1. 1.1Finance and operating leases
  2. 1.2Vehicle renting and its market
  3. 1.3Structure of a leasing transaction
  4. 1.4Players: financial institutions, dealers and manufacturers
  5. 1.5IFRS 16 and accounting treatment
  6. 1.6Legal framework for finance leases
  7. 1.7Products for individuals and businesses
  8. 1.8Risk profile of the automotive portfolio
  9. 1.9Credit, residual and operational risks
  10. 1.10Case study: analysis of a leasing transaction for an SME
  1. 2.1Probability of default (PD)
  2. 2.2Loss given default (LGD)
  3. 2.3Exposure at default (EAD)
  4. 2.4Expected and unexpected loss
  5. 2.5EBA default definition
  6. 2.6Vehicle recovery and its effect on LGD
  7. 2.7Concentration and correlation
  8. 2.8Economic cycle and credit risk
  9. 2.9Regulatory capital under Basel III
  10. 2.10Practice: calculating expected loss for a portfolio
  1. 3.1Transaction admission process
  2. 3.2Creditworthiness analysis for individuals
  3. 3.3Financial analysis of businesses
  4. 3.4Reactive scoring of applications
  5. 3.5Vehicle and transaction variables
  6. 3.6Credit bureau and CIRBE information
  7. 3.7Risk policies and limits
  8. 3.8Machine learning models in admissions
  9. 3.9Responsible lending and the consumer credit directive
  10. 3.10Laboratory: admission scorecard using logistic regression
  1. 4.1Building a scorecard
  2. 4.2Long-term calibration
  3. 4.3Behavioural rating models
  4. 4.4LGD models with vehicle recovery
  5. 4.5Amortisation curves and EAD
  6. 4.6Validation: discrimination and calibration
  7. 4.7IRB models and supervisory requirements
  8. 4.8Model risk
  9. 4.9Model documentation
  10. 4.10Practice: LGD model using remarketing data
  1. 5.1IFRS 9 expected credit loss model
  2. 5.2Staging into Stages 1, 2 and 3
  3. 5.3Significant increase in credit risk
  4. 5.412-month and lifetime expected loss
  5. 5.5Forward-looking macroeconomic scenarios
  6. 5.6Bank of Spain Annex 9
  7. 5.7Post-model adjustments
  8. 5.8Provisions audit
  9. 5.9Reporting to management
  10. 5.10Case study: provisions for a renting portfolio
  1. 6.1Early warning signals of deterioration
  2. 6.2Early-stage arrears management
  3. 6.3Recovery strategies
  4. 6.4Refinancing and restructuring
  5. 6.5Vehicle recovery and remarketing
  6. 6.6Write-off management and portfolio sales
  7. 6.7Vintage delinquency indicators
  8. 6.8Contract fraud
  9. 6.9Consumer protection in recovery
  10. 6.10Workshop: vintage analysis of a portfolio
  1. 7.1Portfolio stress testing
  2. 7.2Risk-adjusted pricing
  3. 7.3Return on risk-adjusted capital (RAROC)
  4. 7.4Securitisation of leasing portfolios
  5. 7.5Electric and technological vehicle risk
  6. 7.6ESG and climate risks in the portfolio
  7. 7.7Insurance linked to the transaction
  8. 7.8Interaction with residual value risk
  9. 7.9Regulatory reporting
  10. 7.10Practice: macroeconomic stress test
  1. 8.1Defining the portfolio under study
  2. 8.2Data preparation
  3. 8.3PD model
  4. 8.4LGD and EAD model
  5. 8.5Expected loss and provisions calculation
  6. 8.6Stress testing
  7. 8.7Proposal for risk policies
  8. 8.8Report for the risk committee
  9. 8.9Dissertation and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and a dedicated technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it possible to combine with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is SAS Credit Scoring, Python (scikit-learn, optbinning), R (scorecard), Moody’s RiskCalc, advanced Excel, in free, academic or evaluation versions. Assignments are based on real procedures: developing an admission scorecard, estimating PD, LGD and EAD with portfolio data, and calculating stage-based provisions under IFRS 9. Assessment is continuous, module by module, plus the final integrating project.

Accredited laboratories(EN ISO/IEC 17025) with rotor test bench, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-driven Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:lecturers with careers in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:safety-by-design approach, cyber-OT, DIH and compliance as core pillars.
Capstone project

Build it end to end

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

Defining the portfolio under study

Describe leasing and renting products and their risk profile.

Data preparation

Explain the fundamentals of credit risk and its measurement.

PD model

Develop applicant admission and scoring models.

LGD and EAD model

Estimate PD, LGD and EAD parameters for automotive portfolios.

Expected loss and provisions calculation

Calculate expected credit loss provisions in accordance with IFRS 9.

Career opportunities

Where this takes you

Credit risk analystScoring modellerTransaction admissions managerRecovery managerIFRS 9 provisions analystRisk model validator
Admissions & scholarships

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 texts.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

FAQ

Frequently asked questions

The programme totals 800 hours spread over 6 to 8 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.

You work with SAS Credit Scoring, Python (scikit-learn, optbinning), R (scorecard), Moody’s RiskCalc, 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 qualification from the Ministry.

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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