Unearned premium risk and machine learning techniques
نویسندگان
چکیده
Insurance companies typically divide premiums into earned and unearned premiums. Unearned premium is the portion of that allocated for remaining period a policy or still needs to be earned. The risk arises when an insufficient cover future losses. Reserves are called deficiency reserves (PDRs). PDR received less attention from actuarial community compared other such as reported but not fully settled (RBNS) claims, incurred (IBNR) claims. Existing research on mainly focused utilizing statistical models. In this article, we apply machine learning models calculate PDR. We use extended warranty dataset, which comes under long-duration P & C insurance contracts demonstrate our Using two models, show predict more accurately than traditional model. Thus, article encourages actuaries consider calculating PDRs risk.
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ژورنال
عنوان ژورنال: Frontiers in Applied Mathematics and Statistics
سال: 2022
ISSN: ['2297-4687']
DOI: https://doi.org/10.3389/fams.2022.1056529