DATA-DRIVEN DECISION-MAKING IN FINANCE

Big data is one of the buzzwords in today’s business world. Since computers became more and more central to modern commerce, businesses have access to large amounts of data, for example, on their customers or transactions. This gives companies the opportunity to extract useful information using statistical and machine learning methods in order to gain a competitive advantage. The big internet companies are the obvious examples, but the topic is also especially relevant for the financial industry (like with credit analysis, fraud detection, insurance and robo-advising). In many areas these new technologies will disrupt existing business models. The course will focus on the analysis of Big Data, and how it can be used for prediction, for example bankruptcies or stock prices. The course will focus on supervised learning techniques such as regression and classification.

Upon completion of this course, students will be able to:

• Practically analyze large-scale business data using machine learning techniques
• Apply basic methods for analyzing data in R
• Apply what they have learned to real finance data
• Use statistical methods for strategic decision making