From Data to Action: AI-Enhanced Prediction of Business Crises Integrating Financial and Social Media Insights

In recent years, various economic and financial upheavals have underscored the need for robust mechanisms to identify and mitigate corporate crises. Particularly, there is a growing recognition of the predictive potential of nonfinancial information, such as data from social media. As contemporary firms extensively use them for communication, these platforms offer valuable insights into evolving crisis situations. Hence, integrating social media-derived information into crisis prediction models is becoming increasingly imperative to enhance firms’ predictive capabilities. This ongoing research, part of a PRIN project, proposes a novel framework for predicting corporate crises by integrating, mainly, financial and social media data through Artificial Intelligence (AI) techniques. Grounded in the context of Italian SMEs, the research aims to enhance the accuracy and timeliness of crisis prediction models and the integration of AI algorithms enables the automated processing and analysis of extensive datasets, facilitating the identification of hidden patterns and early warning signals indicative of impending crises. While emphasizing the importance of financial stability and sustainability, the research also acknowledges the dynamic nature of social media as a source of real-time market sentiment and stakeholder engagement. Despite facing challenges such as data availability and the complexity of AI implementation, the originality of this work lies in its holistic approach, which bridges the gap between different domains to provide a comprehensive framework for crisis prediction tailored to the needs of SMEs in the Italian context.