Applied data science for banking and finance

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The Master’s degree of Applied Data Science for Banking and Finance develops the student’s professional capabilities to leverage the challenges emerging from innovation by using inter-disciplinary competencies. For this reason, the study plan is based on three inter-dependent knowledge based pillars: a technical-scientific area, in order to acquire computer science oriented skills and the instruments for statistical analysis of data; a corporate-management area to develop analytical abilities within a company environment; a financial-economics area to create competences for specific analysis in sectors addressed by this degree course.

Specifically, a student graduating in the Master’s in Applied Data Science for Banking and Finance will be able to support organizational functions to define a company’s strategic decision making operating in banking and financial intermediaries and exploit data analysis techniques and instruments. Additionally, graduates will acquire the necessary  skills to carry out the deployment of financial investment algorithmic strategies, risk management analysis and interpretation of large data volumes, and build systems to predict economic/financial variables on which the decisional processes of the principal actors in the intermediary finance and security market are based.

The Faculty of Banking, Finance and Insurance Science provides teaching, management and research resources, in collaboration with the Faculty of Mathematics, Physics and Natural Sciences, to offer this inter-faculty Master’s degree.

Dean Elena Beccalli explains the benefits of the partnership with Deloitte