MSc in Insurance Data Analysis and Risk Management in Paris
Explore this MSc programme at EBFM Business School, a business school in Paris connecting analytical skills with business decisions.
About the MSc in Insurance Data Analysis & Risk Management
The MSc in Insurance Data Analysis & Risk Management at EBFM Business School combines subject knowledge with case analysis and applied project work.
Develop insurance risk models, multi-source investigation support and governance. Evaluate model performance, digital incidents and organisational controls within authorised investigation settings.
EBFM Business School — European School of Business Finance and Management. Duration: 2 years. Programme reference: ESPAST-27-M.
Building on relevant undergraduate study, the programme develops comparison of methods, work with complex constraints and independent research or applied project management.
Study pathways
Insurance data; business risk; fraud indicators and digital investigation. Pathways share a common core. Applicants indicate their preferred pathway; availability is confirmed before admission.
Learning outcomes
- Analyse policy and claims data to describe loss frequency, severity and changes in risk.
- Build and test insurance risk models, identifying prediction errors, bias and data limitations.
- Investigate unusual claims patterns and recommend checks within authorised procedures.
- Compare underwriting or claims-handling options and explain their costs, risks and effects on customers.
MSc in Insurance Data Analysis & Risk Management: curriculum
Five courses in each of the first three semesters. The fourth semester is devoted to the internship and final assessment.
Year 1 · Semester 1
| Course |
|---|
| 1. Business Research Methods and Academic Writing |
| 2. Business Data Analysis and Statistical Methods |
| 3. Financial Analysis and Business Decisions |
| 4. Corporate Strategy and Organisation Management |
| 5. Business Ethics, Compliance and Data Governance |
Year 1 · Semester 2
| Course |
|---|
| 1. Business Modelling and Scenario Analysis |
| 2. Enterprise Risk Management and Internal Control |
| 3. Business Information Systems and Data Visualisation |
| 4. Insurance Operations and Risk Modelling |
| 5. Insurance Data Analysis and Anomaly Detection |
Year 2 · Semester 3
| Course |
|---|
| 1. Project Management and Organisational Change |
| 2. Investment Appraisal and Performance Management |
| 3. Applied Research and Final Project Design |
| 4. Insurance Internal Control and Risk Governance |
| 5. Insurance Decisions and Risk Model Evaluation |
Year 2 · Semester 4: internship and final assessment
Professional internship, practice report, final project or dissertation, and oral defence. The final project is prepared during semester 3 and completed alongside the internship.
Employed students may apply to use a relevant workplace project for the practice component, subject to academic approval, supervision and assessment.
Projects and practice
Design an insurance risk analysis and investigation-support system, validating models and evidence quality.
Project submissions document the problem, process, individual contribution, validation evidence and limitations. Individual contributions are assessed within team projects. Placements and external projects depend on actual arrangements; no particular employer or placement is guaranteed.
Teaching and assessment
Business cases, data laboratories, scenario analysis and team projects use public, simulated or authorised information. Cases may draw on finance, insurance, industry, telecommunications and healthcare.
Module assignments, cases, practical work, staged projects and the final oral defence assess conceptual accuracy, methods, evidence quality, reliability, communication and reflection. Weightings, reassessment and extension rules are published before teaching begins. Moodle can support resources, assignments, quizzes and feedback; practical activities are recorded and assessed separately.
Entry requirements
Provide evidence of a relevant undergraduate qualification or equivalent experience in business, management, economics, finance, data or a related field. Explain your statistical, analytical and organisational background. Technical investigation pathways also assess networking and data skills.
Submit education evidence, transcripts, a CV, a motivation statement and any required project portfolio. Teaching languages, language evidence and translation requirements are specified in the intake announcement. Website language options do not determine teaching language.
Diploma
Complete the required modules, assessments, final project and applicable academic requirements to receive an institution-issued diploma.
Career development after the MSc in Insurance Data Analysis & Risk Management
Insurance data analyst; business risk analyst; investigation-support analyst. Employment depends on skills, experience and employer requirements; regulated roles also require applicable qualifications and authorisations. Further study is subject to the receiving institution’s admission requirements.