Apply now
CourseInsurance, Risk & Actuarial Data Applications open

Course on the Impact of the AI Act on Mobility Insurance

300-hour online course on the impact of the AI Act on mobility insurance. 6 modules covering Regulation (EU) 2024/1689 on artificial intelligence, Regulation (EU) 2016/679 (GDPR), Art. 22 and Python (Fairlearn). Assigned tutor and open enrolment.

Duration300 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute certificate
Enrol now View syllabus Ask an advisor
Virtual lab · try it before you enrol

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.

SIM · LIVE ●
Learning outcomes

What you will be able to do

01

Explain the structure and timetable of the AI Act.

02

Classify mobility insurance AI use cases by risk level.

03

Apply the obligations for high-risk systems where they apply.

04

Detect and mitigate bias in pricing and claims models.

05

Ensure transparency and human oversight of decisions.

06

Coordinate the AI Act with the GDPR and equality legislation.

07

Design an implementation plan for the Regulation within an organisation.

Profile

Who it's for

  • AI compliance officer wishing to specialise in the Impact of the AI Act on mobility insurance.
  • Algorithm auditor wishing to specialise in the Impact of the AI Act on mobility insurance.
  • Mobility data scientist wishing to specialise in the Impact of the AI Act on mobility insurance.
  • Data protection officer wishing to specialise in the Impact of the AI Act on mobility insurance.
  • Model risk manager wishing to specialise in the Impact of the AI Act on mobility insurance.
  • AI regulatory consultant wishing to specialise in the Impact of the AI Act on mobility insurance.
  • Engineering or science graduates seeking to enter motor and mobility insurance.
Standards & tools

What you'll work with

  • Regulation (EU) 2024/1689 on artificial intelligence
  • Regulation (EU) 2016/679 (GDPR), Art. 22
  • Directive 2004/113/EC (equal treatment in goods and services)
  • Law 15/2022 on comprehensive equal treatment
  • ISO/IEC 42001 (AI management systems)
  • ISO/IEC 23894 (AI risk management)
  • ISO/IEC TR 24027 (bias in AI systems)
Syllabus

6 modules · 300 h

  1. 1.1Structure of the Regulation and its risk-based logic
  2. 1.2Prohibited practices and their scope
  3. 1.3High-risk systems relevant to insurance
  4. 1.4General-purpose AI models
  5. 1.5Obligations by role: provider and deployer
  6. 1.6Interaction with insurance regulation
  7. 1.7Sector vocabulary and acronyms
  8. 1.8Application timetable
  9. 1.9Supervision and penalties
  10. 1.10Exercise: classifying an organisation's systems
  1. 2.1Pricing and risk selection
  2. 2.2Fraud detection
  3. 2.3Claims automation
  4. 2.4Conversational assistants
  5. 2.5Telematics and driving-score models
  6. 2.6Perception systems in insured vehicles
  7. 2.7Damage assessment tools
  8. 2.8Marketing and segmentation
  9. 2.9Classifying each case by risk level
  10. 2.10Practice: inventory and classification of systems
  1. 3.1Risk management system for the model
  2. 3.2Data governance and quality
  3. 3.3Required technical documentation
  4. 3.4Automatic event logging
  5. 3.5Transparency and instructions for use
  6. 3.6Effective human oversight
  7. 3.7Accuracy, robustness and cybersecurity
  8. 3.8Conformity assessment
  9. 3.9Registration in the EU database
  10. 3.10Practice: technical documentation index
  1. 4.1Bias and discrimination in insurance
  2. 4.2Fundamental rights impact assessment
  3. 4.3Right to an explanation of the decision
  4. 4.4Right to human review
  5. 4.5Interaction with data protection
  6. 4.6Informing customers about the use of AI
  7. 4.7Complaints and their management
  8. 4.8Independent model audit
  9. 4.9Documenting design decisions
  10. 4.10Practice: impact assessment of a model
  1. 5.1Model inventory and governance
  2. 5.2Allocation of responsibilities
  3. 5.3Internal AI use policy
  4. 5.4Model supplier control
  5. 5.5Team training
  6. 5.6Continuous monitoring and drift
  7. 5.7Serious incident management
  8. 5.8Internal and supervisory reporting
  9. 5.9Compliance roadmap
  10. 5.10Practice: internal AI use policy
  1. 6.1Selecting the organisation and its systems
  2. 6.2Inventory and risk classification
  3. 6.3Analysis of applicable obligations
  4. 6.4Technical documentation of a system
  5. 6.5Impact and bias assessment
  6. 6.6Designing human oversight
  7. 6.7Governance and training plan
  8. 6.8Compliance roadmap
  9. 6.9Project report
  10. 6.10Project defence
Methodology, software & labs

How you'll learn

100 % online training on the SEIUM campus, with downloadable material, recorded classes and a dedicated 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 regulation and applied exercises. The working software is Python (Fairlearn), SHAP, IBM AI Fairness 360, MLflow, in free, academic or evaluation versions. The tests are studied using real procedures for inventorying and classifying AI systems, bias audits of pricing models and fundamental rights impact assessments. Assessment is continuous, module by module, plus the final integrative project.

Accredited laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-driven Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:teaching staff with a track record 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, ciber-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.

Selecting the organisation and its systems

Explain the structure and timetable of the AI Act.

Inventory and risk classification

Classify mobility insurance AI use cases by risk level.

Analysis of applicable obligations

Apply the obligations for high-risk systems where they apply.

Technical documentation of a system

Detect and mitigate bias in pricing and claims models.

Impact and bias assessment

Ensure transparency and human oversight of decisions.

Career opportunities

Where this takes you

AI compliance officerAlgorithm auditorMobility data scientistData protection officerModel risk managerAI regulatory consultant
Admissions & scholarships

Requirements

  • No prior degree is required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient level of 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.

Apply now Scholarships
FAQ

Frequently asked questions

The programme comprises 300 hours in total, spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.

The course uses Python (Fairlearn), SHAP, IBM AI Fairness 360 and MLflow. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

A SEIUM Institute diploma on passing the continuous assessment and the integrative project. This 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. Please consult the credit transfer policy when enrolling.

Keep exploring

Related programmes

See all in Insurance, Risk & Actuarial Data
Course610 $

Course in Data Analytics for Shared Mobility Insurance

300-hour online course in data analytics for shared mobility insurance. 6 modules covering Regulation (EU) 2016/679 (GDPR), Organic Law 3/2018 (LOPDGDD) and Python (pandas, scikit-learn). Assigned…

300 hOnlineInsurance, Risk & Actuarial Data
Course720 $

Course in Risk Correlation in Global Reinsurance

Online 300-hour course in risk correlation in global reinsurance. 6 modules covering Delegated Regulation (EU) 2015/35 (correlation matrices of the standard formula), Directive 2009/138/EC (Solvency II)…

300 hOnlineInsurance, Risk & Actuarial Data
Course610 $

Course in Risk Coverage in Electric Mobility

Online 300-hour course in risk coverage in electric mobility. 6 modules covering UNECE Regulation No. 100 (electrical safety of vehicles), Regulation (EU) 2023/1542 (batteries and waste…

300 hOnlineInsurance, Risk & Actuarial Data
Course on the Impact of the AI Act on Mobility InsuranceEnrol
Related programmes

More in Insurance, Risk & Actuarial Data

Course in Digital Platforms in Claims ManagementView programme →Course in Underwriting Autonomous Vehicle PoliciesView programme →Course in International Marine Insurance RegulationView programme →Course in Reinsurance Integration with IoT and Big DataView programme →Course in Extreme Risk Models in ReinsuranceView programme →Course on International Regulations on Environmental InsuranceView programme →

All Insurance, Risk & Actuarial Data programmes → · How to apply · Fees & financing · Scholarships

Scroll to Top
SEIUM – Institute of Advanced Engineering
Powered by  GDPR Cookie Compliance
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.