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.
Postgraduate Diploma in Credit Risk in Automotive Leasing — studying from Australia
Australia has a mature insurance and superannuation sector, with major insurers, reinsurers and financial institutions relying heavily on actuarial analysis and risk modelling. Engineers and data specialists contribute to catastrophe modelling, telematics-based pricing and claims analytics, particularly given the country's exposure to bushfire, flood and cyclone risk. The regulatory environment is shaped by prudential oversight and consumer protection frameworks. Employers include general and life insurers, consultancies, reinsurance firms and government risk agencies.
Fees for Australia: A$1,420 (AUD), with instalments and employer sponsorship available.
Relevant bodies in Australia
Typical roles
Questions from Australia
Does this programme lead to recognition by the Actuaries Institute or another Australian professional body?
SEIUM qualifications are private and are not accredited by the Actuaries Institute, Engineers Australia or any national body. The Actuaries Institute sets its own examination and membership requirements, which a private qualification does not replace. Recognition for any role is decided by the employer or the relevant body, so confirm their requirements before enrolling.
Which Australian insurers and risk employers might consider this training?
Insurers, reinsurers, banks, consultancies and risk management teams in Australia employ people with data and risk skills. Whether they consider a private engineering qualification relevant depends on the role and their own hiring policy. Your demonstrated skills, portfolio and final project are often what matter most to them.
Is the course manageable while working, and can my employer fund it?
Yes, the programmes are delivered entirely online in English, with an assigned technical tutor, so you can fit study around work from Australia. Fees can be paid in instalments, and employer sponsorship is possible. Check the total hours for your chosen programme and agree a realistic weekly schedule before you start.
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
Describe leasing and renting products and their risk profile.
Explain the fundamentals of credit risk and its measurement.
Develop applicant admission and scoring models.
Estimate PD, LGD and EAD parameters for automotive portfolios.
Calculate expected credit loss provisions in accordance with IFRS 9.
Design monitoring strategies, early warning systems and debt recovery.
Manage the portfolio considering emerging risks such as the residual value of electric vehicles.
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.
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)
8 modules · 800 h
1.1Finance and operating leases1.2Vehicle renting and its market1.3Structure of a leasing transaction1.4Players: financial institutions, dealers and manufacturers1.5IFRS 16 and accounting treatment1.6Legal framework for finance leases1.7Products for individuals and businesses1.8Risk profile of the automotive portfolio1.9Credit, residual and operational risks1.10Case study: analysis of a leasing transaction for an SME
2.1Probability of default (PD)2.2Loss given default (LGD)2.3Exposure at default (EAD)2.4Expected and unexpected loss2.5EBA default definition2.6Vehicle recovery and its effect on LGD2.7Concentration and correlation2.8Economic cycle and credit risk2.9Regulatory capital under Basel III2.10Practice: calculating expected loss for a portfolio
3.1Transaction admission process3.2Creditworthiness analysis for individuals3.3Financial analysis of businesses3.4Reactive scoring of applications3.5Vehicle and transaction variables3.6Credit bureau and CIRBE information3.7Risk policies and limits3.8Machine learning models in admissions3.9Responsible lending and the consumer credit directive3.10Laboratory: admission scorecard using logistic regression
4.1Building a scorecard4.2Long-term calibration4.3Behavioural rating models4.4LGD models with vehicle recovery4.5Amortisation curves and EAD4.6Validation: discrimination and calibration4.7IRB models and supervisory requirements4.8Model risk4.9Model documentation4.10Practice: LGD model using remarketing data
5.1IFRS 9 expected credit loss model5.2Staging into Stages 1, 2 and 35.3Significant increase in credit risk5.412-month and lifetime expected loss5.5Forward-looking macroeconomic scenarios5.6Bank of Spain Annex 95.7Post-model adjustments5.8Provisions audit5.9Reporting to management5.10Case study: provisions for a renting portfolio
6.1Early warning signals of deterioration6.2Early-stage arrears management6.3Recovery strategies6.4Refinancing and restructuring6.5Vehicle recovery and remarketing6.6Write-off management and portfolio sales6.7Vintage delinquency indicators6.8Contract fraud6.9Consumer protection in recovery6.10Workshop: vintage analysis of a portfolio
7.1Portfolio stress testing7.2Risk-adjusted pricing7.3Return on risk-adjusted capital (RAROC)7.4Securitisation of leasing portfolios7.5Electric and technological vehicle risk7.6ESG and climate risks in the portfolio7.7Insurance linked to the transaction7.8Interaction with residual value risk7.9Regulatory reporting7.10Practice: macroeconomic stress test
8.1Defining the portfolio under study8.2Data preparation8.3PD model8.4LGD and EAD model8.5Expected loss and provisions calculation8.6Stress testing8.7Proposal for risk policies8.8Report for the risk committee8.9Dissertation 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 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.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Describe leasing and renting products and their risk profile.
Explain the fundamentals of credit risk and its measurement.
Develop applicant admission and scoring models.
Estimate PD, LGD and EAD parameters for automotive portfolios.
Calculate expected credit loss provisions in accordance with IFRS 9.
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 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 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.
Related programmes
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…
Diploma in GDPR and Privacy in the Insurance Sector
Online postgraduate diploma of 800 hours in GDPR and privacy in the insurance sector. 8 modules covering Solvency II (Directive 2009/138/EC), IFRS 17 and Delegated Regulation…
Diploma in Insurance Regulation in Asia and Oceania
Online postgraduate diploma of 800 hours in insurance regulation in Asia and Oceania. 8 modules covering fundamentals, the regulatory framework (Solvency II, IFRS 17, Delegated Regulation…
More in Insurance, Risk & Actuarial Data
All Insurance, Risk & Actuarial Data programmes → · How to apply · Fees & financing · Scholarships