Course summary

The MSc in Financial Technology is designed to prepare you for a career in banking and finance with an emphasis in technologies and data management. In addition to the fundamental skills and knowledge of finance, you will be exposed to leading-edge concepts in artificial intelligence (AI), blockchain (cryptocurrencies), and big data analysis among other emerging topics. The curriculum draws on GCU’s expertise in diverse areas of finance including regulation, risk analysis, modelling, and securities and investments within the framework of systems architecture, software development, and data management. The content and teaching strategies are designed to help you gain the essential skills and knowledge to prepare you to grow as a professional within the changing landscape of the banking and finance industry. Advances in technology have brought about radical changes to financial operations, products and services. Key amongst them are activities such as the provision of credit (disintermediation through peer-to-peer lending and crowdfunding), payment systems (blockchain technology and digital currencies), investments (algorithmic trading, online stockbroking services), and personal finance (robo-advisory services for individual investors). These innovations depend on secure and efficient communication systems and the processing of large amounts of data via machine learning algorithms. The modules in this course will help you gain an understanding of the evolving nature of financial technologies: impact on financial rules and regulation, analysing and managing financial risk, current and emerging trends in different financial sectors as well as challenges and opportunities to the subject and practice of finance. On an equal basis, the course's modules focus on enhancing your skills and knowledge of software development, artificial intelligence, data visualisation and ethics, putting these into practice to solve real-world problems. This course will enable you to: Critically apply concepts of machine learning, neural networks, data science algorithms, advanced exploratory statistics to solve financial problems with applications of computational intelligence. Evaluate the latest software development methodologies and apply the appropriate process to the information system needs of banking and financial institutions. Critically analyse information collection techniques and analysis methods and manipulate and develop tools and technologies designed for capturing, processing, storing, transferring, analysing, and visualising data for financial applications. Develop a workable knowledge base and skills in areas of current technological development in finance (such as blockchain, distributed ledger technology, cybersecurity, payment systems and so on) as applied to risk analysis and modelling, regulation, compliance, and investment analysis.