Data Privacy and Ethics in Telematics Insurance Course
Online 300 h course in data privacy and ethics in telematics insurance. 6 modules covering Regulation (EU) 2016/679 (GDPR), Organic Law 3/2018 (LOPDGDD) and OneTrust. Assigned tutor and enrolment open.
Data Privacy and Ethics in Telematics Insurance Course — studying from New Zealand
New Zealand's insurance and financial services sector is concentrated in Auckland and Wellington, with a strong focus on general insurance, life insurance and risk management. Natural hazard risk, particularly from earthquakes, is a major consideration, and the Earthquake Commission provides residential natural disaster cover. Actuarial and risk data professionals work for insurers, reinsurers, regulators and consultancies, with oversight from the Reserve Bank of New Zealand and the Financial Markets Authority.
Fees for New Zealand: NZ$1,470 (New Zealand dollar), with instalments and employer sponsorship available.
Relevant bodies in New Zealand
Typical roles
Questions from New Zealand
Which New Zealand bodies recognise actuarial and risk qualifications?
The Actuarial Society of New Zealand and the New Zealand Institute of Actuaries work alongside international bodies such as the Institute and Faculty of Actuaries. Membership and professional credentials in these fields are set by those bodies, not by private providers. SEIUM's qualifications are private and not accredited by any national body, so their standing depends on how your employer or the relevant body assesses them.
Do insurers and financial firms in New Zealand hire people with data and risk skills?
New Zealand's insurance, banking and government sectors do employ people in risk, pricing and data analysis, and the Reserve Bank and insurers both draw on these skills. Hiring usually depends on demonstrated technical ability and professional credentials. A SEIUM qualification can support your application, but whether it is valued is up to each employer.
How is the programme delivered and paid for?
The programme is 100% online and taught in English, so no student visa is needed to study from New Zealand. You are assigned a technical tutor and complete a final project. Fees are payable in instalments, and employer sponsorship is possible. Time commitment varies by programme, from 300 hours for specialist courses to 1,900 hours for master's programmes.
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
Identify what data a telematics insurance policy collects and for what purpose.
Determine the appropriate legal basis for each data processing activity.
Design transparent and understandable information for the policyholder.
Analyse the ethical dilemmas of behaviour-based pricing.
Establish governance and security measures for telematics data.
Carry out a data protection impact assessment.
Develop a final project on a privacy and ethics audit.
Who it's for
- Data protection officer at an insurer who wishes to specialise in Data privacy and ethics in telematics insurance.
- Telematics product manager who wishes to specialise in Data privacy and ethics in telematics insurance.
- Privacy consultant who wishes to specialise in Data privacy and ethics in telematics insurance.
- Data protection auditor who wishes to specialise in Data privacy and ethics in telematics insurance.
- Data ethics analyst who wishes to specialise in Data privacy and ethics in telematics insurance.
- Information security manager who wishes to specialise in Data privacy and ethics in telematics insurance.
- Graduates in engineering or science seeking to enter telematics insurance.
What you'll work with
- Regulation (EU) 2016/679 (GDPR)
- Organic Law 3/2018 (LOPDGDD)
- EDPB Guidelines 01/2020 on connected vehicles
- Directive 2002/58/EC (privacy in electronic communications)
- Regulation (EU) 2023/2854 (Data Act)
- Directive 2004/113/EC (equal treatment in goods and services)
- ISO/IEC 27701 (privacy information management)
6 modules · 300 h
1.1Devices and sources: black box, dongle, app and manufacturer data1.2Driving variables: speed, braking, acceleration and night-time use1.3Location data and its particular sensitivity1.4Derived inferences: habitual journeys, routines and places visited1.5Legitimate uses: pricing, prevention, claims and assistance1.6Questionable uses: commercial segmentation and transfer to third parties1.7Data lifecycle in a telematics insurer1.8Stakeholders: insurer, technology provider and manufacturer1.9Data that would not need to be collected for the same purpose1.10Workshop: inventory of processing activities for a telematics product
2.1Lawfulness of processing: contract, legitimate interest and consent2.2Why consent is not always the appropriate basis2.3Data minimisation and purpose limitation in telematics2.4Retention periods and effective erasure2.5Controllers and processors in the telematics chain2.6Third-party data: other drivers and occupants2.7Disclosures to reinsurers, garages and loss adjusters2.8International transfers and cloud providers2.9Policyholder rights: access, portability and objection2.10Guided reading of an information clause for a telematics product
3.1What the customer must understand before installing the device3.2Layers of information and plain language3.3Explainability of the driving score3.4Communicating data-based premium changes3.5User dashboards and access to their own information3.6Managing expectations: what the insurer sees and what it does not3.7Minors, occasional drivers and shared vehicles3.8Withdrawal of consent and its effect on the contract3.9Customer complaints about the use of their data3.10Practice: redesigning the information for a real product
4.1Actuarial fairness versus perceived fairness4.2Behavioural variables versus protected characteristics4.3Indirect discrimination by time of day, neighbourhood or road type4.4Effect of telematics on vulnerable groups4.5Algorithmic transparency and the right to an explanation4.6Automated decisions and human intervention4.7Incentives: when to reward and when to penalise4.8Perceived surveillance and driver autonomy4.9Self-imposed ethical limits within the sector4.10Guided debate on a penalty scheme
5.1Data governance policy in an insurer5.2Information classification and access control5.3Pseudonymisation and separation of identifiers5.4Security of the device and the transmission channel5.5Security at the telematics provider: clauses and auditing5.6Breach management: detection, notification and communication5.7Record of processing activities5.8Traceability of data use in claims5.9Use of telematics data as evidence in a claim5.10Practical case: breach at the telematics provider
6.1When an impact assessment is mandatory6.2Methodology: context, necessity, risks and measures6.3Consultation with the data protection officer6.4Proportionate technical and organisational measures6.5Privacy by design in a new telematics product6.6Internal audit and periodic review of processing6.7Documentation required by the supervisory authority6.8Relationship with European artificial intelligence regulation6.9Training of sales and claims teams6.10Final project: impact assessment of a telematics product
How you'll learn
Fully 100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it possible to combine study with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is OneTrust, Python (pandas), advanced Excel, PILAR (risk analysis), in free, academic or evaluation versions. Case studies are based on real data protection impact assessment procedures, transparency audits of telematics apps and ethical reviews of behaviour-based pricing. 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.
Identify what data a telematics insurance policy collects and for what purpose.
Determine the appropriate legal basis for each data processing activity.
Design transparent and understandable information for the policyholder.
Analyse the ethical dilemmas of behaviour-based pricing.
Establish governance and security measures for telematics data.
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.
You will work with OneTrust, Python (pandas), advanced Excel and PILAR (risk analysis). Free, academic or evaluation versions are used, and the tutor will indicate the open-source alternative where one exists.
An own SEIUM 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 recognised in the advanced programme. Please check the recognition policy when you enrol.
Related programmes
Course in Motor Insurance Loss Assessment
Online 300-hour course in motor insurance loss assessment. 6 modules covering Royal Legislative Decree 8/2004 (civil liability and motor vehicle insurance), Law 35/2015 (traffic valuation table)…
Course on Customer Segmentation in Mobility Insurance
Online course of 300 hours in customer segmentation in mobility insurance. 6 modules covering Regulation (EU) 2016/679 (GDPR), Regulation (EU) 2024/1689 (Artificial Intelligence Regulation) and Python…
Machine Learning Course Applied to Motor Insurance
Online 300-hour course in machine learning applied to motor insurance. 6 modules covering Regulation (EU) 2024/1689 on artificial intelligence, Regulation (EU) 2016/679 (GDPR) and Python (scikit-learn).…
More in Insurance, Risk & Actuarial Data
All Insurance, Risk & Actuarial Data programmes → · How to apply · Fees & financing · Scholarships