Assessing Skip-Tracing Information in Repossession Prediction Using Ensemble Learning and SHAP Analysis
Predictive modeling for auto-repossession risk has received little academic attention despite its operational importance. When a vehicle cannot be located, repossession companies often rely on skip-tracing, an established industry practice that uses third-party data sources such as license plate rec...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IEEE
2026-01-01
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| coleção: | IEEE Access |
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| Acesso em linha: | https://ieeexplore.ieee.org/document/11589248/ |
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