Global Finance Analytics MSc PG Dip

The finance industry is evolving at a rapid rate with transformations coming from big data analytics and digital techniques. The 100% online Global Finance Analytics MSc, Postgraduate Diploma ties together the key principles of finance with the cutting-edge analytical concepts needed to thrive in today’s financial world. Building on financial foundations, you will explore contemporary aspects including artificial intelligence, investment analysis, big data, machine learning, and fintech developments. Studying this course will enable you to apply highly desirable learnt skills and knowledge to real-world financial situations, relevant today and in the future. Finance analytics provides a promising job landscape globally with fast-growing demand for employees with these skills. As technology continues to reach new heights, knowledge from this course will be essential well into the years ahead of us. For further information please email us on onlineenrolmentservice@kcl.ac.uk or call +44 20 7848 7860

Key benefits

• Finance experts are essential across a range of industries, but companies are placing importance on data, searching out employees who can offer forward-thinking, predictive insights to shape the business practices of today and in the future. This course unlocks these skills, addressing the growing demand for analytics professionals.
• Global Finance Analytics MSc/PG Dip has been designed in close collaboration with leading financial industry practitioners and covers the fundamentals of advanced analytics in finance. Topics covered include big data techniques with a focus on applications in business and conduct risk management, as well as product origination and trading decision making. You will also explore more advanced topics such as robo-advice and fintech developments.
• A focus for teaching will be placed on reflective skills that not only enable students to assimilate methods but also allow them to identify their appropriate utility in a variety of real-world situations. This will be possible via real-world case studies, simulation exercises (including R and Python coding opportunities) and more. The modular design of the course provides both core topics and the chance for you to choose from a range of optional modules, depending on your own goals.

Further information