The Small Business Act of the European Commission in 2008 (https://ec.europa.eu/growth/smes/business-friendly-environment/small-business-act_en) acknowledges the key role of Small and Medium Enterprises (SMEs) in the European Union economy. This is particularly true for Italy, which has the largest share of SMEs in Europe, as well as for other countries such as Portugal, Spain and Greece. On the other hand, SMEs experience more difficulties in their early stages mainly due to high market competition and credit constraints.

For these reasons, the study of SMEs default risk is always on the agenda. The literature concentrates mainly on financial indicators built on businesses' balance sheets, which are available about two years late with respect to their reference period. This diminishes the significance of the results, both for credit risk and policy aims, and particularly in a forecasting perspective.

The purpose of this project is to assess to what extent firms' default can be predicted adding to the traditional data sources (offline information) data collected from their corporate websites (online information). The online indicators can be obtained via web scraping and content analysis techniques of corporate websites. We will therefore develop a new method of monitoring a firm by automatically obtaining an indicator of its health status derived from its corporate websites. This way, we could design a model for nowcasting businesses’ default.