Federico Ricciuti

Nicola Lavecchia, Sid Fadanelli, Federico Ricciuti et al.

Generative AI technologies have demonstrated significant potential across diverse applications. This study provides a comparative analysis of credit score modeling techniques, contrasting traditional approaches with those leveraging generative AI. Our findings reveal that current generative AI models fall short of matching the performance of traditional methods, regardless of the integration strategy employed. These results highlight the limitations in the current capabilities of generative AI for credit risk scoring, emphasizing the need for further research and development before the possibility of applying generative AI for this specific task, or equivalent ones.

Federico Ricciuti

Many studies suggest that LLMs have left wing leans. The article extends previous analysis of US presidential elections considering several virtual elections in multiple European countries. The analysis considers multiple LLMs and the results confirm the extent of the leaning. Furthermore, the results show that the leaning is not uniform between countries. Sometimes, models refuse to take a position in the virtual elections, but the refusal rate itself is not uniform between countries.