The MSc Financial Data Science programme is intended for students with an interest in the impact of technology on markets and the business environment, who wish to pursue a career in the finance or insurance sectors.  The programme aims to provide students with the skills, knowledge and background to begin a career in FinTech and Financial Data Science and progress quickly to leadership roles (Purpose).  The educational values of the programme are to provide students with the knowledge and skills to; appraise, evaluate and manage opportunities in the emerging FinTech landscape; employ software skills and leading-edge data science packages to inform key business decisions in finance and insurance, including investment decisions, risk management and lending decisions; develop a deep understanding of the Economic underpinnings of the finance and insurance sectors; appreciate the legal, regulatory, accounting and taxation aspects of finance and the impact of the FinTech and RegTech revolution on these areas; develop the cultural, negotiation and organisational expertise to operate in a truly global business; and communicate effectively with peers (Education and subject/discipline/professional values).  The learning environment combines theoretical knowledge with application to real world financial data sets.   In many cases, the theory in lectures will be further enhanced by small group tutorials.   Furthermore, industry leaders will contribute to the programme through guest lectures and invited seminars.  Internship and FinTech incubator options are further integrated into the programme (the nature of the learning environment for students).  The programme uses multiple teaching, learning and assessment approaches.  Assessment strategies include traditional exams, case study presentations and written reports.  Group projects and presentations are also a key feature of this programme (key approaches to teaching, learning and assessment).

1 - Articulate and explain current theory and practice underpinning the impact of technology on the finance and insurance sectors (FinTech and Financial Data Science).
2 - Analyse and model aspects of the FinTech sector by drawing on a variety of frameworks, concepts and tools.
3 - Critically assess the functional aspects of FinTech and Financial Data Science.
4 - Query, analyse and model using complex financial data sets to inform key business decisions.
5 - Quantitatively assess the results of applying data science and financial machine learning to complex data sets.
6 - Qualitatively assess the legal, economic and accounting frameworks underlying the FinTech and RegTech sectors.
7 - Synthesise and summarise data, information and results from data science models and professionally communicate outcomes of the analysis & their recommendations to key stakeholders.
8 - Select and use appropriate communication strategies (oral, written & visual) to effectively communicate to peers.
9 - Effectively engage and contribute in multicultural teams.
10 - Identify ways to add value in industry, drawing on the broad skills developed while undertaking the programme.
11 - Engage in continuous professional development and the enhancement of skills and competencies required for personal success in business today.

Students must complete 10 core modules (60 ECTS) in Autumn and Spring trimesters. In summer trimester students must complete Ethics in Financial Services (FIN41930, 7.5 ECTS) and choose one of three pathways:
1. Green Data Science (FIN41910) plus 2 x 7.5 ECTS option modules OR
2. Green Data Science (FIN41910) plus Summer Internship (FIN42060, 15 ECTS) OR
3. Undertake a FinTech Incubator Project (FIN42140, 25 ECTS). Places on summer modules will be made available for online registration in March.

Module ID	Module Title	Trimester	Credits
Stage 1 Core Modules
FIN41660	Financial Econometrics	Autumn	5
FIN42020	Derivative Securities	Autumn	5
FIN42030	Financial Analysis	Autumn	5
FIN42040	Capital Markets & Instruments	Autumn	5
FIN42050	Quant. Methods for Finance	Autumn	5
FIN42330	Python for Fin. Data Science	Autumn	5
FIN41360	Portfolio & Risk Mgt	Spring	7.5
FIN42100	Machine Learning for Finance	Spring	7.5
FIN42110	Data Science for Trading & Risk Management	Spring	7.5
FIN42130	Banking& Finance inDigital Age	Spring	7.5
FIN41910	Green Data Science	Summer	7.5
FIN41930	Ethics in Financial Services	Summer	7.5
Stage 1 Core Modules
Stage 1 Options - A)MIN1OF: Choose 2 x 7.5 ECTs options modules. If you would like to pursue Summer Internship (FIN42060) or FinTech Incubator Project (FIN42140), your Programme Manager will register you upon approval. Students will be able to register to Summer Trimester modules in March.
FIN40490	Advanced Treasury Management/Financial Engineering	Summer	7.5
FIN41480	Mergers & Acquisitions	Summer	7.5
FIN41950	Financial Technology	Summer	7.5
FIN42060	Summer Internship	Summer	15
FIN42140	FinTech Product Development Project	Summer	25
FIN42210	Structured Finance	Summer	7.5
FIN42340	Business Communications	Summer	7.5
Stage 1 Options - A)MIN1OF: Choose 2 x 7.5 ECTs options modules. If you would like to pursue Summer Internship (FIN42060) or FinTech Incubator Project (FIN42140), your Programme Manager will register you upon approval. Students will be able to register to Summer Trimester modules in March.

		Award		GPA
Programme	Module Weightings	Rule Description	Description
MTBUS005	Stage 1 - 100.00%	Standard Honours Award	First Class Honours	3.68	4.20
			Second Class Honours, Grade 1	3.08	3.67
			Second Class Honours, Grade 2	2.48	3.07
			Pass	2.00	2.47