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.
Course on the Impact of the AI Act on Mobility Insurance — studying from Canada
Canada has a major insurance and financial services sector, with headquarters and operations concentrated in Toronto and Montréal. Insurers and reinsurers rely on actuarial science, risk modelling and data analytics for pricing, reserving and capital management. Federal and provincial regulators oversee solvency, conduct and consumer protection. Engineers and data specialists with risk and modelling skills find roles at insurers, brokers, consultancies and regulatory bodies.
Fees for Canada: C$852 (Canadian dollar), with instalments and employer sponsorship available.
Relevant bodies in Canada
Typical roles
Questions from Canada
Is this programme recognised by professional bodies in Canada for insurance and actuarial data work?
SEIUM's qualifications are private, not official state degrees, and are not accredited by a national body in Canada. Actuarial credentials in Canada are governed by the Canadian Institute of Actuaries, and actuarial practice is regulated under provincial and federal rules. A private engineering qualification does not confer these credentials, so confirm recognition with employers or the relevant body yourself.
How might this qualification be used by employers in Canada in insurance or risk roles?
Insurers, banks and risk teams in Canada may value engineering-based data analysis and risk modelling skills, but how they regard a private qualification is their decision. Hiring in these sectors often depends on experience, professional exams and specific credentials. Your final project can serve as evidence of applied skills, though it does not guarantee any role or salary outcome.
What are the practical demands of studying this online from Canada?
Study is fully online and in English, and no student visa is required if you study from home. Programme lengths range from 300 to 1,900 hours, so consider how many hours a week you can commit alongside work. You are assigned a technical tutor for support. Fees can be paid in instalments, and some students receive employer sponsorship, which is possible but not guaranteed.
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
Explain the structure and timetable of the AI Act.
Classify mobility insurance AI use cases by risk level.
Apply the obligations for high-risk systems where they apply.
Detect and mitigate bias in pricing and claims models.
Ensure transparency and human oversight of decisions.
Coordinate the AI Act with the GDPR and equality legislation.
Design an implementation plan for the Regulation within an organisation.
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.
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)
6 modules · 300 h
1.1Structure of the Regulation and its risk-based logic1.2Prohibited practices and their scope1.3High-risk systems relevant to insurance1.4General-purpose AI models1.5Obligations by role: provider and deployer1.6Interaction with insurance regulation1.7Sector vocabulary and acronyms1.8Application timetable1.9Supervision and penalties1.10Exercise: classifying an organisation's systems
2.1Pricing and risk selection2.2Fraud detection2.3Claims automation2.4Conversational assistants2.5Telematics and driving-score models2.6Perception systems in insured vehicles2.7Damage assessment tools2.8Marketing and segmentation2.9Classifying each case by risk level2.10Practice: inventory and classification of systems
3.1Risk management system for the model3.2Data governance and quality3.3Required technical documentation3.4Automatic event logging3.5Transparency and instructions for use3.6Effective human oversight3.7Accuracy, robustness and cybersecurity3.8Conformity assessment3.9Registration in the EU database3.10Practice: technical documentation index
4.1Bias and discrimination in insurance4.2Fundamental rights impact assessment4.3Right to an explanation of the decision4.4Right to human review4.5Interaction with data protection4.6Informing customers about the use of AI4.7Complaints and their management4.8Independent model audit4.9Documenting design decisions4.10Practice: impact assessment of a model
5.1Model inventory and governance5.2Allocation of responsibilities5.3Internal AI use policy5.4Model supplier control5.5Team training5.6Continuous monitoring and drift5.7Serious incident management5.8Internal and supervisory reporting5.9Compliance roadmap5.10Practice: internal AI use policy
6.1Selecting the organisation and its systems6.2Inventory and risk classification6.3Analysis of applicable obligations6.4Technical documentation of a system6.5Impact and bias assessment6.6Designing human oversight6.7Governance and training plan6.8Compliance roadmap6.9Project report6.10Project defence
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.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Explain the structure and timetable of the AI Act.
Classify mobility insurance AI use cases by risk level.
Apply the obligations for high-risk systems where they apply.
Detect and mitigate bias in pricing and claims models.
Ensure transparency and human oversight of decisions.
Where this takes you
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.
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.
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