My study path is related to Statistics and Machine learning techniques applied to socio-economic data. The main topics of interest are ESG performance, greenwashing and sustainable AI. The current line of research is focused on the analysis of different types of data (structured and non structered) in order to determine the main drivers of greenwashing. Other topics of interest: AI applied to banking supervision; ESG risks in banking.

The main objective is to identify the drivers of greenwashing and to develop recommendations that can help consumers spot the companies engaged in greenwashing, regulators to prevent such practices and investors to avoid companies that provide misleading information. In order to estimate the risk of greenwashing, two types of data on ESG performance of companies are analyzed: self-disclosed data and those provided by external stakeholders.