MSc in Insurance Data Analysis & Risk Management
Explore this MSc programme at FINCOM Paris, a business school in Paris connecting analytical skills with business decisions.
Programme overview
Develop insurance risk models, multi-source investigation support and governance. Evaluate model performance, digital incidents and organisational controls within authorised investigation settings.
FINCOM Paris — Paris College of Commerce and Financial 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
- Apply risk models to prediction, validation and bias, documenting methods, evidence and the basis for professional judgement.
- Apply business intelligence to events and multi-source information, documenting methods, evidence and the basis for professional judgement.
- Apply investigation methods to evidence, authorisation and traceability, documenting methods, evidence and the basis for professional judgement.
- Apply organisational controls to processes, permissions and monitoring, documenting methods, evidence and the basis for professional judgement.
- Apply decision evaluation to scenarios, costs and impacts, documenting methods, evidence and the basis for professional judgement.
- Apply governance research to model risk and reporting, documenting methods, evidence and the basis for professional judgement.
Learning content and competency modules
| Module | Learning content | Assessment evidence |
|---|---|---|
| Risk models | Prediction, validation and bias. Advanced research and complex project analysis. | Problem definition and analytical report |
| Business intelligence | Events and multi-source information. Advanced research and complex project analysis. | Reproducible case or model file |
| Investigation methods | Evidence, authorisation and traceability. Advanced research and complex project analysis. | Data and operational records with quality checks |
| Organisational controls | Processes, permissions and monitoring. Advanced research and complex project analysis. | Option comparison and testing evidence |
| Decision evaluation | Scenarios, costs and impacts. Advanced research and complex project analysis. | Project plan and collaboration records |
| Governance research | Model risk and reporting. Advanced research and complex project analysis. | Final report and oral defence |
Study progression
- Year 1: deepen risk models, business intelligence, investigation methods; undertake literature or case research and define the project question and approach.
- Year 2: integrate organisational controls, decision evaluation, governance research through an independent research or applied project, final report and oral defence.
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
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.
Tuition and fees
Contact admissions for the tuition and payment terms applicable to your chosen programme before enrolment.
Applications
Select this programme and study level when submitting a preliminary application. The admissions office reviews materials and contacts the applicant. A preliminary application is not an admission decision or a payment commitment.
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