Overview
Financial analytics arms decision makers with the tools to make sense of an increasingly complex world. By combining internal financial information and operational data with external information such as social media, demographics and big data, financial analytics may address critical business questions with unprecedented ease, speed, and accuracy.
The Master of Science (MSc) in Financial Analysis has been designed to meet the growing need for financial professionals with the practical skills required for a rapidly evolving data driven financial function. Upon completion of this programme, graduates will understand the core principles of finance, be equipped to utilise data analytics, machine learning, and visualisation tools, apply the appropriate financial analytic models, and acquire enhanced understanding of business decision making in an ethical and cyber context.
Both full time and part time programme options are designed to facilitate learners with a Mathematic/Economic/computing/technology background who wish to upskill in this new and emerging area of Financial Analytics. Students can opt to take the theory and practical modules only and not complete the dissertation.
Aims of the Programme
The overall aim of the programme is to produce graduates with strong proficiencies in the application of financial analytics in a contemporary and evolving data driven environment, while also enhancing practical and technical skills.
The Master of Science (MSc) in Financial Analytics programme specific aims are to:
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Enable learners to develop in-depth knowledge and analytical skills in current and developing financial technologies.
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Provide learners with the ability to think critically and make informed, value creating, decisions based on complex and voluminous data.
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Develop learners’ core competencies and technical skills in the fields of applied finance, quantitative modelling risk management techniques and financial statement analysis.
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Enhance the learner’s ability to operate effectively in cross-cultural settings, understand the nature and complexities of globalisation with an ongoing commitment to the importance of business ethics in a global financial business environment.
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Foster learners’ leadership characteristics which will enable graduates to lead teams and to achieve organisational goals.
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Create an innovative and entrepreneurial mind-set that will enable learners to solve real problems in an evolving, technologically driven work environment.
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Enable learners to identify, develop and apply detailed analytical, creative, problem solving and research skills.
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Provide learners with a comprehensive platform for career development, innovation and further study.
Delivery
This programme is taught on a hybrid basis. This means learners are timetabled either in-class or online, in a mix of online and in-class days.
Entry Requirements
The minimum entry requirements for the Master of Science (MSc.) in Financial Analytics are:
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A Level 8 primary cognate degree with a minimum second-class second-division (2.2) classification from a recognised third level institution. Cognate subjects include business, accountancy, computing, information systems, engineering, general science, mathematics, statistics, data analytics or related discipline.
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Graduates of any non-cognate discipline and hold a qualification in a conversion-style programme such as the DBS Higher Diploma in Science in FInTech
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For applicants whose first language is not English and who have not previously undertaken a degree taught through English, evidence must be provided of proficiency in English language equivalent to B2+ or above on the Common European Framework of Reference for Languages (CEFRL). This must be evidenced through a recognised English Language test such as IELTS, Cambridge Certificate, PTE or DBS English Assessment. Test certificates should be dated within the last two years to be considered valid.
Applicants who do not have a Level 8 qualification in a cognate area and who have at least 3 years’ work experience may also be considered through the college’s normal RPL procedures. Relevant professional experience may be taken into account and individuals will be assessed on a case-by-case basis through DBS RPL procedures.