MSc Finance Analytics

At King’s College London, MSc Finance Analytics isn’t just about lectures and theory. From day one you’ll get hands-on exposure to data, markets, and the tools finance professionals actually use. The programme builds your quantitative and empirical finance skills, especially in big data analytics — but you’ll also get access to top-tier infrastructure and support designed to mirror what firms expect.

• The course is built around big-data methods applied to real financial problems — risk management, product origination, trading, forecasting via text or data mining, automation, robo-trading, and FinTech innovations.

• You’ll work with real-time financial data and market intelligence thanks to KCL’s “Trading Room” setup, which gives students access to the same databases and platforms used by finance professionals, including Bloomberg and Refinitiv.

• The programme teaches technical and programming skills — such as data analytics, visualization, big data techniques, and coding for finance applications.

So you don’t just read about modern finance — you do it, using the tools and data you’ll one day use on the job.

📚 Concrete Components — What you study and how it's structured

Here’s how the MSc is structured, embedding practical work and technical training:

Core and Optional Modules

You’ll complete modules totaling 180 credits, including:

Required modules include:

• Introduction to Analytics in Finance

• Principles of Finance

• Big Data Analytics and Visualisation

• Business Risk Analytics

• A 60-credit Dissertation (major project)

Options (you choose based on your interests):

• Big Data and Text Business & Finance Analytics

• FinTech Analytics and Robo Trading

• Conduct Risk Management

• Other electives like Empirical Finance, Corporate Finance, Financial Econometrics, Portfolio Management, Mathematical Finance, Risk Management for Data Analytics, and more.

Teaching & Assessment Methods

• A blend of lectures, seminars, case discussions, and class activities — not just passive listening.

• Assessments come in many forms: written examinations, coursework, individual and group projects, presentations, case studies. This ensures you practice both technical analysis and real-world problem solving.

• The dissertation — a substantial research/analysis project under one-to-one supervision — gives a chance to apply everything you’ve learned to a real finance-analytics problem.

 Facilities, Tools & Industry Integration

One of the biggest strengths of MSc Finance Analytics at King’s is what you get beyond the textbooks:

• Trading Room with Bloomberg & Refinitiv / Real-Time Market Data: Students access professional financial platforms used by banks, investment firms, and asset managers worldwide.

• Software Access: Through King’s IT and library resources you have access to software and data-analysis tools like Python, R (RStudio), MATLAB, Stata, EViews, and other quantitative / econometric tools.

• Extensive Data & Research Databases: King’s provides major financial and market data databases (equity, derivatives, historical data, macro data, ESG data, company-level data, etc.), plus academic journals and e-books for both coursework and dissertation research.

• Location & Industry Proximity: The programme is located in central London — close to the financial district, FinTech firms, and global financial institutions, which provides excellent opportunities for networking, internships, and exposure to real-world finance environments.

• Careers Support via Dedicated Programmes: Postgraduate finance students have access to structured career support, including case-practice, CV/resume building, interview preparation, and access to the Trading Room to develop finance-market skills.

 Who It's Best For & What You Get at the End

This programme is ideal if:

• You already have a strong quantitative or analytical background (finance, economics, math, engineering, or data science).

• You want to combine finance + data analytics + technology — aiming for careers such as quantitative analyst, risk analyst, FinTech specialist, data-driven finance roles, trading, portfolio management, or financial research.

• You are looking for industry-relevant training and tools, not just theory — learning how to handle big data, use professional finance databases, build visualisations, perform empirical analysis, and work on real-world finance problems.

By the time you graduate, you’ll walk away not just with a “master’s degree” — but with a portfolio of real analytic work, hands-on experience with finance-industry tools, and exposure to market data and professional workflows. This makes you highly employable in finance, FinTech, data-driven banking, asset management, consulting, or any sector where finance and data intersect.

Graduates from the MSc Finance Analytics at King’s College London step into careers that blend finance, data analysis, and technology. Many begin as analysts in financial data, quantitative research, or risk management, and over time progress into roles such as Quantitative Strategist, Risk Manager, Data-Driven Portfolio Manager, or FinTech Analytics Lead.

Typical job roles include:

• Financial Data Analyst

• Quantitative Finance Analyst

• Risk Analyst

• FinTech / Trading Analytics Associate

How King’s prepares you for strong employment outcomes:

• Dedicated King’s Business School Careers Team, offering CV and cover-letter refinement, interview training, and specialised workshops for analytics and finance careers.

• Strong employability outcomes, as the programme is designed around real industry needs, combining finance fundamentals with high-demand skills like coding, big-data analysis, and financial modelling.

• Industry-engaged curriculum, with modules developed alongside practising finance professionals, ensuring you’re trained on real market problems and employer expectations.

• Future-proof skillset — the mix of programming, data analytics, econometrics, and finance theory aligns perfectly with analytics-driven roles in modern banking, investment firms, and FinTech companies.

• Long-term value through global recognition, as a King’s degree carries weight with employers worldwide and signals strong analytical and quantitative abilities.

Further Academic Progression:

After completing this programme, students commonly advance into MPhil or PhD studies in Finance, Quantitative Finance, Financial Economics, or Data Science, especially if they’re aiming for careers in research, quantitative modelling, or academia. Others pursue professional qualifications — such as CFA, FRM, or specialised data-science certifications — to accelerate their pathway into senior analyst, risk-management, or finance-technology leadership roles.