Heribert Valero Lapaz, egresado del Grado en Estadística Empresarial y Data Scientist en BBVA Data & Analytics, ha colaborado recientemente en el proyecto «Urban Lens».

Urban Lens explores millions of anonymized financial transactions in Spain based on data provided by BBVA, which holds a ubiquitous banking infrastructure in the country. The data provides an opportunity to uncover macro trends derived from a fine-grained scale of individual economic behavior. In light of the failure of past decades to produce models that effectively predict and explain the macroeconomic trends, we noticed that a gap exists between models of micro behaviors and macro phenomena. This project performs a comparative analysis of city microeconomics, aiming to elucidate how bigger economic patterns could be understood utilizing data of individual economic transactions.

Researchers at the Senseable City Lab built a novel multi-scale predictive model of Spanish regions, quantifying the distinctive signature of each region based on their spending behavior by identifying indicators regarding the amount of spending, type of spending, type of individual, and individual mobility. The model was validated at the provincial scale using official performance statistics, and proved a strong correlation between individual spending behavior and official socioeconomic indices. Finally, a scale-free clustering was developed to enable a consistent aggregation of regions in different spatial dimensions.

Urban Lens holds tremendous potential in its far-reaching applicability to discover patterns that can be used in urban planning, policy-making and business decisions. The web application allows users to explore these indicators and cluster regions based on their distinctive economic signature.

Más información en  http://senseable.mit.edu/urban-lens/