Abstract
This paper describes the current mass information environment, the so-called Big Data, in which financial institutions move today and analyses the new opportunities that this situation generates for banks and financial institutions to use the new data available on their present and potential clients to improve their marketing strategies. The new forms of available information are described, which include not only traditional numerical data tables, but images, web texts and temporal and spatial data, sometimes in the form of functions. These new data can reveal patterns of behaviour and relationships between variables that allow better customer segmentation and build models with greater predictive capacity than current ones. Some of the new tools developed in recent years under the names of statistical learning, artificial intelligence, and machine learning are briefly reviewed and their potential in different problems, such as personalized prediction, customer network analysis, fraud prevention or customer loyalty detection. Finally, an example is presented of how the construction of customer networks and their analysis can improve trade policies in a large international bank.
