Comparing Credit Risk Estimates in the Gen-AI Era
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866908399792291840 |
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| author | Lavecchia, Nicola Fadanelli, Sid Ricciuti, Federico Aloe, Gennaro Bagli, Enrico Giuffrida, Pietro Vergari, Daniele |
| author_facet | Lavecchia, Nicola Fadanelli, Sid Ricciuti, Federico Aloe, Gennaro Bagli, Enrico Giuffrida, Pietro Vergari, Daniele |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_07754 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Comparing Credit Risk Estimates in the Gen-AI Era Lavecchia, Nicola Fadanelli, Sid Ricciuti, Federico Aloe, Gennaro Bagli, Enrico Giuffrida, Pietro Vergari, Daniele Machine Learning Artificial Intelligence 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. |
| title | Comparing Credit Risk Estimates in the Gen-AI Era |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2506.07754 |