Financial Risk Management MSc

UCL (University College London)

Finance is driven by technology. Becoming an expert in both will enable you to thrive in risk management roles in the financial sector. The Financial Risk Management MSc brings together traditional theories in finance, data analytics, quantitative and computational modelling techniques – designed to produce talented practitioners in this field. A distinctive finance programme taught from a computer science perspective, the Financial Risk Management MSc trains you to become an expert in computing, quantitative finance, and technology to manage and predict financial risk. You'll experience an innovative programme that combines core financial concepts with cutting-edge computational techniques and technologies, through topics such as machine learning, algorithmic trading and blockchain. Learning from renowned lecturers who also undertake research or are practitioners in the finance industry, you'll gain a core understanding of market risk, credit risk, operational risk, systemic risk, and financial engineering, complemented by topics that range from market microstructure to probability, stochastic processes, and data-driven modelling. You'll also combine knowledge about how the financial system works with computational techniques. You'll undertake a substantial project as part of your programme, bringing opportunities to work with an industry partner on a real-world problem, or to embark on an academic research project supervised by one of our leading academics. This programme gives you key skills to become a professional in financial markets and related technical aspects, while you immerse yourself in London life and the benefits of living in a global financial centre. This programme is ideal for you if you have a first degree in mathematics, finance, economics, physics, or computing and wish to gain the skills necessary to work within quantitative risk management. You will be expected to have established competency in probability, statistics, differential equations, and the use of a computer to solve numerical problems.

Engineering Sciences