MSc in Financial Data Analysis & Business Intelligence

Explore this MSc programme at FINCOM Paris, a business school in Paris connecting analytical skills with business decisions.

Programme overview

Develop financial data research, multi-source business intelligence and decision support. Evaluate risk indicators, events and digital threats, connecting analytical models with investigation evidence, governance and secure communication.

FINCOM Paris — Paris College of Commerce and Financial Management. Duration: 2 years. Programme reference: ESPAST-26-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

Financial data analysis; business intelligence; financial risk and digital threats. Pathways share a common core. Applicants indicate their preferred pathway; availability is confirmed before admission.

Learning outcomes

• Apply financial modelling to scenarios, validation and limitations, documenting methods, evidence and the basis for professional judgement.
• Apply multi-source intelligence to relationships, events and analysis, documenting methods, evidence and the basis for professional judgement.
• Apply threat investigation to incidents, evidence and responsibilities, documenting methods, evidence and the basis for professional judgement.
• Apply risk governance to controls, compliance and reporting, documenting methods, evidence and the basis for professional judgement.
• Apply decision support to uncertainty and comparison of options, documenting methods, evidence and the basis for professional judgement.
• Apply analytical project to reproducibility, review and dissemination, documenting methods, evidence and the basis for professional judgement.

Learning content and competency modules

Study progression

• Year 1: deepen financial modelling, multi-source intelligence, threat investigation; undertake literature or case research and define the project question and approach.
• Year 2: integrate risk governance, decision support, analytical project through an independent research or applied project, final report and oral defence.

Projects and practice

Study business and digital risks in a financial organisation, submitting analytical models, evidence and decision recommendations.

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

Financial data analyst; business intelligence analyst; digital risk 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.