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An incremental loss ratio method using prior information on calendar year effects
In a run-off triangle external factors can have a similar influence on all incremental losses of the same calendar year. This can distort the triangle such that reserving methods like chain ladder or the loss ratio method do not work properly. A very recent example of such an external factor is the...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119846/ https://www.ncbi.nlm.nih.gov/pubmed/35611236 http://dx.doi.org/10.1007/s13385-022-00315-3 |
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author | Riegel, Ulrich |
author_facet | Riegel, Ulrich |
author_sort | Riegel, Ulrich |
collection | PubMed |
description | In a run-off triangle external factors can have a similar influence on all incremental losses of the same calendar year. This can distort the triangle such that reserving methods like chain ladder or the loss ratio method do not work properly. A very recent example of such an external factor is the Covid-19 pandemic. In many countries, the insurance industry is in the process of establishing market knowledge about the impact of the pandemic on premiums and losses. We extend the additive claims reserving model to allow for calendar year effects and develop a variant of the incremental loss ratio method (also known as the additive method) that can make use of such market knowledge. We derive formulas for the mean squared error of prediction and provide a detailed numerical example. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13385-022-00315-3. |
format | Online Article Text |
id | pubmed-9119846 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-91198462022-05-20 An incremental loss ratio method using prior information on calendar year effects Riegel, Ulrich Eur Actuar J Original Research Paper In a run-off triangle external factors can have a similar influence on all incremental losses of the same calendar year. This can distort the triangle such that reserving methods like chain ladder or the loss ratio method do not work properly. A very recent example of such an external factor is the Covid-19 pandemic. In many countries, the insurance industry is in the process of establishing market knowledge about the impact of the pandemic on premiums and losses. We extend the additive claims reserving model to allow for calendar year effects and develop a variant of the incremental loss ratio method (also known as the additive method) that can make use of such market knowledge. We derive formulas for the mean squared error of prediction and provide a detailed numerical example. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13385-022-00315-3. Springer Berlin Heidelberg 2022-05-20 2023 /pmc/articles/PMC9119846/ /pubmed/35611236 http://dx.doi.org/10.1007/s13385-022-00315-3 Text en © EAJ Association 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Paper Riegel, Ulrich An incremental loss ratio method using prior information on calendar year effects |
title | An incremental loss ratio method using prior information on calendar year effects |
title_full | An incremental loss ratio method using prior information on calendar year effects |
title_fullStr | An incremental loss ratio method using prior information on calendar year effects |
title_full_unstemmed | An incremental loss ratio method using prior information on calendar year effects |
title_short | An incremental loss ratio method using prior information on calendar year effects |
title_sort | incremental loss ratio method using prior information on calendar year effects |
topic | Original Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119846/ https://www.ncbi.nlm.nih.gov/pubmed/35611236 http://dx.doi.org/10.1007/s13385-022-00315-3 |
work_keys_str_mv | AT riegelulrich anincrementallossratiomethodusingpriorinformationoncalendaryeareffects AT riegelulrich incrementallossratiomethodusingpriorinformationoncalendaryeareffects |