Diploma in Risk Assessment in Multimodal Transport
Online postgraduate diploma of 800 hours in risk assessment in multimodal transport. 8 modules covering the fundamentals, the regulatory framework (Solvency II, IFRS 17, Delegated Regulation (EU) 2015/35), analysis methods, design, systems integration, reliability and risk, validation and an integrative case study, with an assigned technical tutor.
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
Master the technical fundamentals of risk assessment in multimodal transport and their regulatory vocabulary.
Apply Solvency II (Directive 2009/138/EC), IFRS 17 and Delegated Regulation (EU) 2015/35 to real design and validation decisions.
Build and correlate calculation models with R and Python (pandas, scikit-learn).
Plan and run test campaigns in an actuarial modelling environment and a claims data platform.
Analyse operating data and turn it into engineering decisions.
Prepare the technical and compliance dossier required by the client or the regulator.
Lead a project in risk assessment in multimodal transport from start to finish.
Who it's for
- Non-life actuaries looking to specialise in risk assessment in multimodal transport.
- Risk analysts who want to broaden their technical profile in this field.
- Technical underwriters assessing the associated risks.
- Claims adjusters who need deeper technical knowledge of the subject.
- Pricing managers modelling the risks involved.
- Technical reserves managers.
- Engineering or science graduates looking to move into motor insurance.
What you'll work with
- Solvency II (Directive 2009/138/EC) (EU prudential regime for insurers)
- IFRS 17 (accounting standard for insurance contracts)
- Delegated Regulation (EU) 2015/35 (Solvency II implementing rules)
- EIOPA Guidelines (European insurance supervisory guidance)
- ISO 31000 (risk management)
- Law 20/2015 – LOSSEAR (Spanish law on the supervision of insurers)
- Regulation (EU) 2016/679 – GDPR (personal data protection)
- DORA – Regulation (EU) 2022/2554 (digital operational resilience)
- AI Act – Regulation (EU) 2024/1689 (artificial intelligence)
- R
- Python (pandas, scikit-learn)
- SAS
- Prophet
- ResQ
8 modules
1.1Core concepts and quantities of Risk Assessment in Multimodal Transport1.2Technology landscape and state of the art1.3Technical terminology and reference documentation1.4Physical and engineering principles applied to the case1.5Functional architecture: from requirements to components1.6Interfaces and dependencies with adjacent systems1.7Typical use cases in the sector1.8Common errors and how to detect them early1.9Data sources and quality criteria1.10Guided exercise: initial diagnosis
2.1Applicable regulatory framework: overview2.2Regulatory hierarchy and conflicts between standards2.3Mandatory requirements versus good practice2.4Acceptance criteria and required evidence2.5Technical documentation and traceability2.6Change management and configuration control2.7Audits, inspections and non-conformities2.8Responsibilities and division of scope2.9Interpretation of critical clauses2.10Exercise: regulatory checklist
3.1Setting up the model: assumptions and simplifications3.2Selection of tools and working environment3.3Preparation of input data3.4Workflow and modelling good practice3.5Discretisation and case preparation3.6Boundary conditions and load cases3.7Convergence control and numerical verification3.8Sensitivity analysis and parametric study3.9Automation and model reuse3.10Exercise: building a base model
4.1Design requirements and starting criteria4.2Solution alternatives and comparative analysis4.3Sizing and safety margins4.4Selection of materials, equipment or components4.5Integration with the rest of the system4.6Cost, schedule and manufacturing constraints4.7Reliability, maintainability and service life4.8Sustainability and efficiency in design4.9Design review and risk management4.10Exercise: documented design proposal
5.1System architecture and functional breakdown5.2Interface definition and control5.3Protocols and data exchange5.4Progressive integration and interface testing5.5Electromagnetic and environmental compatibility5.6Configuration management of the complete system5.7Resolving conflicts between subsystems5.8Tuning of the integrated system5.9Traceability from requirements to verification5.10Exercise: interface matrix
6.1Hazard identification and preliminary analysis6.2Failure modes and effects analysis6.3Fault trees and quantitative analysis6.4Allocation of reliability targets6.5Barriers, redundancies and fault tolerance6.6Human factors and operating errors6.7Safety evidence and argumentation6.8Risk management throughout the life cycle6.9Indicators and in-service monitoring6.10Exercise: risk analysis of a case
7.1Verification and validation strategy7.2Test plan: scope and coverage7.3Instrumentation and data acquisition7.4Laboratory testing versus field testing7.5Correlation between model and measurement7.6Handling uncertainty and tolerances7.7Failure analysis and corrective actions7.8Commissioning and acceptance criteria7.9Documenting the validation file7.10Exercise: validation report
8.1Case definition and success criteria8.2Gathering input data and requirements8.3Work planning and deliverables8.4Technical development guided by the tutor8.5Applying the regulatory framework to the case8.6Verification of results and critical analysis8.7Documenting the deliverable8.8Technical defence and peer review8.9Lessons learned and continuous improvement8.10Final project: final assessment and programme close-out
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: you progress at your own pace within the intake, so you can combine it with your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is R, Python (pandas, scikit-learn), SAS, Prophet and ResQ, in free, academic or evaluation versions. Testing is studied on real procedures in an actuarial modelling environment, a claims data platform and a catastrophe scenario simulator. Assessment is continuous by module, plus the final integrative project.
Standards covered: Solvency II (Directive 2009/138/EC), IFRS 17, Delegated Regulation (EU) 2015/35, EIOPA Guidelines, ISO 31000, Law 20/2015 (LOSSEAR), Regulation (EU) 2016/679 (GDPR), DORA (Regulation (EU) 2022/2554), AI Act (Regulation (EU) 2024/1689).
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- An internet connection and a computer capable of running the programme 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.
Frequently asked questions
The programme totals 800 hours over 6–8 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 (pandas, scikit-learn), SAS, Prophet and ResQ, 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 final project. 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 are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the programme 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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