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Master’s in Data Protection and Privacy in Data-Driven Insurance Engineering

Online master's programme of 1,900 hours in data protection and privacy engineering for data-driven insurance: 12 modules covering personal data in insurance, the GDPR and LOPDGDD, accountability, automated decision-making, privacy-enhancing techniques, information security, international transfers, telematics and health data, data ethics and rights management, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Identify personal data processing activities in insurance.

02

Apply the GDPR and the LOPDGDD to data-driven products.

03

Carry out impact assessments and apply privacy by design.

04

Safeguard rights in automated decision-making and profiling.

05

Apply anonymisation, pseudonymisation and differential privacy techniques.

06

Manage international transfers and security breaches.

07

Design ethical frameworks for data use in insurers.

Profile

Who it's for

  • Data protection officers at insurers and insurtechs.
  • Privacy consultants serving the insurance sector.
  • Information security managers responsible for policyholder data.
  • Data protection lawyers advising on data-driven products.
  • Data governance analysts working with telematics, health or IoT data.
  • Privacy auditors.
  • Engineering or science graduates seeking to enter the insurance sector.
Standards & tools

What you'll work with

  • Regulation (EU) 2016/679 (GDPR, data protection)
  • Organic Law 3/2018 (LOPDGDD, Spanish data protection and digital rights law)
  • Regulation (EU) 2024/1689 (Artificial Intelligence Act)
  • ISO/IEC 27701:2019 (privacy information management)
  • ISO/IEC 27001:2022 (information security management)
  • Regulation (EU) 2023/2854 (Data Act)
  • Regulation (EU) 2022/2554 (DORA, digital operational resilience)
  • Regulation (EU) 2025/327 (European Health Data Space)
  • OneTrust
  • ARX Data Anonymization Tool
  • PILAR (CCN-CERT)
  • Python (SDV)
  • Microsoft Purview
Syllabus

12 modules · 1900 h

  1. 1.1Data life cycle in the insurer
  2. 1.2Health, biometric and genetic data
  3. 1.3Location and telematics data
  4. 1.4Home IoT data
  5. 1.5Third-party data and enrichment
  6. 1.6Risk profiles and segmentation
  7. 1.7Industry-wide databases
  8. 1.8Data in claims and fraud
  9. 1.9Risks to data subjects' rights
  10. 1.10Case study: inventory of an insurer's processing activities
  1. 2.1GDPR principles
  2. 2.2Legal bases for processing
  3. 2.3Special categories of data
  4. 2.4Organic Law 3/2018
  5. 2.5Insurance sector rules on data
  6. 2.6Consent in insurance
  7. 2.7Legitimate interest and the balancing test
  8. 2.8Data subjects' rights
  9. 2.9AEPD sanctions regime
  10. 2.10Workshop: analysis of legal bases by processing activity
  1. 3.1Record of processing activities
  2. 3.2Data protection officer
  3. 3.3Privacy by design and by default
  4. 3.4Data protection impact assessment (DPIA)
  5. 3.5Management of processors
  6. 3.6Joint controllership
  7. 3.7Policies and procedures
  8. 3.8Training and awareness
  9. 3.9Privacy audits
  10. 3.10Practical exercise: DPIA for a telematics insurance product
  1. 4.1Article 22 of the GDPR
  2. 4.2Profiling in pricing
  3. 4.3Human intervention
  4. 4.4Right to explanation
  5. 4.5Algorithmic transparency
  6. 4.6Proxy discrimination
  7. 4.7The AI Act and life and health insurance
  8. 4.8European Data Protection Board guidelines
  9. 4.9Relevant European case law
  10. 4.10Case study: review of an automated underwriting decision
  1. 5.1Pseudonymisation
  2. 5.2Anonymisation and re-identification risk
  3. 5.3K-anonymity and l-diversity
  4. 5.4Differential privacy
  5. 5.5Synthetic data
  6. 5.6Homomorphic encryption
  7. 5.7Secure multi-party computation
  8. 5.8Federated learning
  9. 5.9Secure data environments
  10. 5.10Lab: anonymising a policy database
  1. 6.1ISO/IEC 27001 and 27002
  2. 6.2ISO/IEC 27701 privacy information management
  3. 6.3Access control
  4. 6.4Encryption and key management
  5. 6.5Cloud security
  6. 6.6Logging and monitoring
  7. 6.7Security breach management
  8. 6.8Notification to the AEPD and to data subjects
  9. 6.9DORA and ICT risk
  10. 6.10Practical exercise: breach management procedure
  1. 7.1GDPR transfer regime
  2. 7.2Adequacy decisions
  3. 7.3Standard contractual clauses
  4. 7.4Transfer impact assessment
  5. 7.5Binding corporate rules
  6. 7.6EU-US Data Privacy Framework
  7. 7.7Global cloud providers
  8. 7.8Reinsurance and transfers
  9. 7.9Multinational groups
  10. 7.10Case study: transferring data to a foreign reinsurer
  1. 8.1Connected vehicle data
  2. 8.2EDPB guidelines on connected vehicles
  3. 8.3The Data Act and data access
  4. 8.4Location and journeys
  5. 8.5Information to the driver
  6. 8.6Secondary drivers
  7. 8.7Data retention
  8. 8.8Use in claims and fraud
  9. 8.9Sharing with manufacturers
  10. 8.10Workshop: privacy notice for usage-based insurance
  1. 9.1Health questionnaires
  2. 9.2Genetic data and prohibitions
  3. 9.3Wearables and wellness programmes
  4. 9.4European Health Data Space
  5. 9.5Health data in claims
  6. 9.6Communication with healthcare providers
  7. 9.7Right to be forgotten for cancer survivors
  8. 9.8Medical confidentiality
  9. 9.9Risk of discrimination
  10. 9.10Practical exercise: designing a compliant wellness programme
  1. 10.1Data governance and privacy
  2. 10.2Data ethics committees
  3. 10.3Ethical principles in data use
  4. 10.4Algorithmic fairness
  5. 10.5Data monetisation and its limits
  6. 10.6Data sharing in ecosystems
  7. 10.7Open insurance
  8. 10.8Customer trust
  9. 10.9Privacy indicators
  10. 10.10Case study: ethical framework for the use of external data
  1. 11.1Procedure for exercising rights
  2. 11.2Access and portability
  3. 11.3Rectification and erasure
  4. 11.4Objection and restriction
  5. 11.5Deadlines and identity verification
  6. 11.6Complaints before the AEPD
  7. 11.7Sanctioning procedures
  8. 11.8Communication with data subjects
  9. 11.9Automating rights management
  10. 11.10Practical exercise: responding to a complex access request
  1. 12.1Selection of the processing activity or product
  2. 12.2Analysis of the legal framework
  3. 12.3Data map and flows
  4. 12.4Impact assessment
  5. 12.5Design of technical measures
  6. 12.6Design of organisational measures
  7. 12.7Implementation plan
  8. 12.8Conclusions
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

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 it fits around your job.

Each module combines theory, guided reading of the original regulations and applied exercises. The working software is OneTrust, ARX Data Anonymization Tool, PILAR (CCN-CERT), Python (SDV) and Microsoft Purview, in free, academic or evaluation versions. Exercises are based on real procedures: impact assessments for data-driven insurance products, anonymisation and synthetic data generation, and management of security breaches and data subjects' rights. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: Regulation (EU) 2016/679 (GDPR), Organic Law 3/2018 (LOPDGDD), Regulation (EU) 2024/1689 (AI Act), ISO/IEC 27701:2019, ISO/IEC 27001:2022, Regulation (EU) 2023/2854 (Data Act), Regulation (EU) 2022/2554 (DORA), Regulation (EU) 2025/327 (European Health Data Space).

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of the GDPR, the LOPDGDD, the AI Act and ISO/IEC 27701 applied to real cases, not as a theoretical annex.
Industry software:OneTrust, ARX Data Anonymization Tool, PILAR (CCN-CERT), Python (SDV) and Microsoft Purview, in free, academic or evaluation versions.
Master's Thesis with defence:A complete privacy compliance design for a data-driven insurance product or processing activity, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Legal framework analysis
Select a processing activity or product and analyse its legal bases and applicable rules.
Data map and flows
Map the personal data and its flows, including transfers to third parties.
Impact assessment
Carry out a DPIA covering automated decisions and re-identification risks.
Technical and organisational measures
Design privacy-enhancing techniques, security controls and an implementation plan.
Master's Thesis
A complete privacy compliance design for a data-driven insurance product, defended before a panel.
Career opportunities

Where this takes you

Data protection officerInsurance privacy consultantInformation security managerData protection lawyerData governance analystPrivacy auditor
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • 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.

Apply now Scholarships
FAQ

Frequently asked questions

The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with OneTrust, ARX Data Anonymization Tool, PILAR (CCN-CERT), Python (SDV) and Microsoft Purview, 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 Master's Thesis. 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 in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.

A degree in engineering, science or architecture (or equivalent professional experience), 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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