Course in Mobility Insurance in Smart Cities
300-hour online course in mobility insurance in smart cities. 6 modules covering Royal Legislative Decree 8/2004 (civil liability and motor vehicle insurance), Directive 2009/103/EC (motor vehicle insurance), amended by Directive (EU) 2021/2118, and Python (pandas). Personal tutor assigned and enrolment open.
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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 the mobility modes of a smart city and their risks.
Apply the liability and compulsory insurance regime to new modes of transport.
Design products for multimodal users and shared fleets.
Use urban and telematics data in pricing.
Manage claims in shared mobility environments.
Assess collaboration between insurers, operators and city councils.
Present an insurance product for the mobility of a specific city.
Who it's for
- Mobility insurance product manager who wishes to specialise in Mobility Insurance in Smart Cities.
- Urban data analyst who wishes to specialise in Mobility Insurance in Smart Cities.
- Pricing actuary who wishes to specialise in Mobility Insurance in Smart Cities.
- Partnerships manager with city councils and operators who wishes to specialise in Mobility Insurance in Smart Cities.
- Mobility claims manager who wishes to specialise in Mobility Insurance in Smart Cities.
- Smart cities consultant who wishes to specialise in Mobility Insurance in Smart Cities.
- Graduates in engineering or sciences seeking to enter insurance companies.
What you'll work with
- Royal Legislative Decree 8/2004 (civil liability and motor vehicle insurance)
- Directive 2009/103/EC (motor vehicle insurance), amended by Directive (EU) 2021/2118
- Law 35/2015 (damages assessment scale)
- Law 7/2021 on climate change and energy transition (low-emission zones)
- Regulation (EU) 2016/679 (GDPR)
- ISO 37120 (sustainable city indicators)
- Directive (EU) 2016/97 (IDD)
6 modules · 300 h
1.1From private car ownership to service: how risk changes1.2Shared vehicles, motorbike sharing, e-scooters and bicycles1.3Public transport, taxis and chauffeur-driven vehicles1.4Last-mile delivery and commercial fleets1.5Micromobility: real accident rates and typical injuries1.6Autonomous vehicles and allocation of liability1.7Low-emission zones and their effect on the vehicle fleet1.8City data and available sources1.9Stakeholders: city council, operator, user and insurer1.10Exercise: risk map of an urban mobility service
2.1Compulsory insurance and its fit with new vehicles2.2Legal classification of personal mobility vehicles2.3Municipal ordinances and their variation between cities2.4Liability of the fleet operator2.5User liability and terms of use2.6Accidents involving pedestrians and protection of the most vulnerable third party2.7Insurance required of delivery services2.8Data protection in connected services2.9Litigation and trends in case law2.10Practice: analysing the real coverage of a rental service
3.1From annual insurance to usage-based insurance3.2Per-minute, per-trip and per-kilometre insurance3.3Coverage embedded in the operator's app3.4Parametric insurance and automated payment3.5Excesses, limits and exclusions that customers understand3.6Fleet product versus end-user product3.7Pricing and segmentation3.8Automated underwriting and frictionless onboarding3.9Pre-contractual transparency and plain language3.10Practice: designing a usage-based product for e-scooters
4.1Data sources: vehicle, phone and platform4.2Driving variables and their real predictive power4.3Behaviour-based pricing models4.4Model bias and price fairness4.5Consent and minimisation of collected data4.6Automatic accident detection4.7Claim reconstruction using platform data4.8Prevention and user alerts that genuinely change behaviour4.9Measuring the impact on accident rates without fooling yourself4.10Practice: defining the data model of a telematics product
5.1Claim notification from the app itself5.2Digital claims handling and automation5.3Repair, replacement and garage network5.4Fraud in micromobility and warning signs5.5Management of minor injuries and third-party claims5.6Recovery between operators5.7Customer service for a low-value product5.8Profitability: management cost versus premium collected5.9Portfolio monitoring indicators5.10Practice: designing the claims process from start to finish
6.1Choice of city and service6.2Risk analysis and expected claims6.3Legal framework applicable in that city6.4Product and coverage design6.5Data and pricing model6.6Claims flow and service levels6.7Projected profit and loss account6.8Launch plan6.9Project report6.10Final defence of the work
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: students progress at their own pace within the intake, which makes it possible to combine the course with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (pandas), QGIS, Power BI, Geotab (telematics), in free, academic or evaluation versions. Case studies draw on real urban accident analysis procedures using open data, and on designing a product for multimodal users. Assessment is continuous 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 the mobility modes of a smart city and their risks.
Apply the liability and compulsory insurance regime to new modes of transport.
Design products for multimodal users and shared fleets.
Use urban and telematics data in pricing.
Manage claims in shared mobility environments.
Where this takes you
Requirements
- No prior qualification 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 totals 300 hours spread over 3 to 5 months. That is between 10 and 15 hours a week on average, compatible with full-time work.
The course uses Python (pandas), QGIS, Power BI, Geotab (telematics). Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM own diploma on passing continuous assessment and the integrating project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the advanced programme. Check the credit transfer policy when you enrol.
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