Classification problem in liability insurance using machine learning models: a comparative study
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Accesso online: | |
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| _version_ | 1866929571633299456 |
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| author | Qazvini, Marjan |
| author_facet | Qazvini, Marjan |
| contents | Underwriting is one of the important stages in an insurance company. The insurance company uses different factors to classify the policyholders. In this study, we apply several machine learning models such as nearest neighbour and logistic regression to the Actuarial Challenge dataset used by Qazvini (2019) to classify liability insurance policies into two groups: 1 - policies with claims and 2 - policies without claims. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_00354 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Classification problem in liability insurance using machine learning models: a comparative study Qazvini, Marjan Applications Machine Learning Underwriting is one of the important stages in an insurance company. The insurance company uses different factors to classify the policyholders. In this study, we apply several machine learning models such as nearest neighbour and logistic regression to the Actuarial Challenge dataset used by Qazvini (2019) to classify liability insurance policies into two groups: 1 - policies with claims and 2 - policies without claims. |
| title | Classification problem in liability insurance using machine learning models: a comparative study |
| topic | Applications Machine Learning |
| url | https://arxiv.org/abs/2411.00354 |