The world of finance is changing. With recent advances in technology, huge amounts of data are generated every second on a global scale. Finance professionals of the future will need to harness advanced technologies to process, analyse and ultimately extract key insights to tackle the challenges facing the industry. Students will acquire the knowledge and develop the skills and expertise needed for a broad range of careers in finance and other multinational organisations. With a focus on big data analytics, our Finance Analytics MSc is designed to provide you with rigorous applied training in quantitative and empirical methods in Finance. This course is suited to individuals with strong quantitative backgrounds who desire the skills & expertise needed for a range of highly skilled technical professions in finance. You'll study topics at the cutting edge of the finance industry such as data visualisation, big data, FinTech and robo-trading. We also offer the fully online Global Finance Analytics MSc, PG Dip if the on-campus course is not suitable for you.
Key benefits
- Our course is designed to provide you with rigorous applied training in quantitative and empirical methods in finance, with a focus on big data analytics.
- Learn about the internal workings of corporations, financial institutions and financial services firms, and their inter-relationships.
- Become familiar with latest development in FinTech and automation, including Robo- advice and trading.
- Located in the heart of London, King’s Business School has a strong reputation for research-led teaching and close links to the financial industry.
Our MSc in Finance Analytics offers a unique combination of a rigorous academic programme that teaches the recent developments in data analytics and a unique practitioners’ view of how these developments are shaping the practical aspects of finance. For example, the programme teaches big data methods with applications to risk management, product origination, and trading; text mining techniques with applications to forecasting; automation techniques with applications to robo-advice/trading; and FinTech developments in banking. Graduates will thus gain knowledge and skills that are highly sought after by financial industry firms, including incumbent large financial institutions as well as disruptor/start-ups focusing on innovation. In addition, given the importance of analytics in a broader context, the course provides skills that can be used across a wide range of industries outside Finance, including e-commerce, hospitality, retail, pharmaceutical, and media. Student employability is one of the main focuses of the Programme. Firstly, the Programme has been designed in close collaboration with leading financial industry practitioners. Second, active senior finance industry practitioners participate in the teaching of a large proportion of the modules. Third, the Programme offers additional ungraded modules that enhance students’ programming skills as well as their understanding of financial markets. This course is best suited for students with strong mathematical skills and quantitative backgrounds, such as finance, mathematics, engineering, computer science, and economics.
Course Aims
- Provide rigorous applied training in quantitative and empirical methods in finance, with a focus on big data analytics.
- Explore the internal workings of corporations, financial institutions and financial services firms, and their inter-relationships.
- Analyse the latest development in FinTech and automation, including Robo- advice and trading.