Evaluating Reserve Risk in a Regulatory Perspective
We propose statistical methods for estimating not only the moments but the whole distribution of Claims Development Results (CDR), which is a key variable in calculating economic capital for non-life insurance reserving risk. These methods allow us to provide estimates of the under-provisioning risk...
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| Veröffentlicht in: | Journal of insurance issues 2015-10, Vol.38 (2), p.157-183 |
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| container_title | Journal of insurance issues |
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| creator | Koenig, Emmanuel Le Moine, Pierre Monfort, Alain Ratiarison, Eric |
| description | We propose statistical methods for estimating not only the moments but the whole distribution of Claims Development Results (CDR), which is a key variable in calculating economic capital for non-life insurance reserving risk. These methods allow us to provide estimates of the under-provisioning risk, or reserve risk, associated with each accident year and of the global reserve risk. These risks are measured by the Value at Risk of the opposite of the CDR. We carefully examine the impact of two kinds of potential mistakes : wrongly assuming normality of the variables of interest and ignoring updating of the estimates of the parameters appearing in the statistical model. We show that both kinds of error may lead to large underestimations of the risk and, therefore, of the economic capital for reserving risk. These findings seem particularly important in a regulatory perspective. |
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These methods allow us to provide estimates of the under-provisioning risk, or reserve risk, associated with each accident year and of the global reserve risk. These risks are measured by the Value at Risk of the opposite of the CDR. We carefully examine the impact of two kinds of potential mistakes : wrongly assuming normality of the variables of interest and ignoring updating of the estimates of the parameters appearing in the statistical model. We show that both kinds of error may lead to large underestimations of the risk and, therefore, of the economic capital for reserving risk. These findings seem particularly important in a regulatory perspective.</description><identifier>ISSN: 1531-6076</identifier><identifier>EISSN: 2332-4244</identifier><language>eng</language><publisher>Northridge: Western Risk and Insurance Association</publisher><subject>Accidents ; Capital ; Consistent estimators ; Estimation methods ; Estimators ; Insurance regulation ; Insurance risk ; Life insurance ; Maximum likelihood estimation ; Parametric models ; Risk management ; Solvency ; Statistical methods ; Statistical variance ; Studies</subject><ispartof>Journal of insurance issues, 2015-10, Vol.38 (2), p.157-183</ispartof><rights>Copyright © Western Risk and Insurance Association, 2015</rights><rights>Copyright Western Risk & Insurance Association Fall 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/43574413$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/43574413$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,57995,58228</link.rule.ids></links><search><creatorcontrib>Koenig, Emmanuel</creatorcontrib><creatorcontrib>Le Moine, Pierre</creatorcontrib><creatorcontrib>Monfort, Alain</creatorcontrib><creatorcontrib>Ratiarison, Eric</creatorcontrib><title>Evaluating Reserve Risk in a Regulatory Perspective</title><title>Journal of insurance issues</title><description>We propose statistical methods for estimating not only the moments but the whole distribution of Claims Development Results (CDR), which is a key variable in calculating economic capital for non-life insurance reserving risk. 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These findings seem particularly important in a regulatory perspective.</description><subject>Accidents</subject><subject>Capital</subject><subject>Consistent estimators</subject><subject>Estimation methods</subject><subject>Estimators</subject><subject>Insurance regulation</subject><subject>Insurance risk</subject><subject>Life insurance</subject><subject>Maximum likelihood estimation</subject><subject>Parametric models</subject><subject>Risk management</subject><subject>Solvency</subject><subject>Statistical methods</subject><subject>Statistical variance</subject><subject>Studies</subject><issn>1531-6076</issn><issn>2332-4244</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNotjl9rgzAUxcNYYa7rRxgE9izkJjeJPo7S_YHCRum7RE1E59QlKvTbL6x7Ood7fpx7bkjCheApcsRbkoAUkCqm1R25D6FjDLjIVULEYTX9YuZ2aOjJButXS09t-KLtQE28NEtv5tFf6Kf1YbLV3K72gWyc6YPd_euWnF8O5_1bevx4fd8_H9MmA0i1NhnLS5Q1coVlhnXpmKiM0yqzVeUc4yU4UJVVmEekzhF0tEbKmhuViS15utZOfvxZbJiLblz8ED8WoCUH0IgQqccr1YW4s5h8-238pUAh_2LxCw1DSiw</recordid><startdate>20151001</startdate><enddate>20151001</enddate><creator>Koenig, Emmanuel</creator><creator>Le Moine, Pierre</creator><creator>Monfort, Alain</creator><creator>Ratiarison, Eric</creator><general>Western Risk and Insurance Association</general><general>Western Risk & Insurance Association</general><scope>3V.</scope><scope>4U-</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88C</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>M0C</scope><scope>M0T</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>S0X</scope></search><sort><creationdate>20151001</creationdate><title>Evaluating Reserve Risk in a Regulatory Perspective</title><author>Koenig, Emmanuel ; 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These methods allow us to provide estimates of the under-provisioning risk, or reserve risk, associated with each accident year and of the global reserve risk. These risks are measured by the Value at Risk of the opposite of the CDR. We carefully examine the impact of two kinds of potential mistakes : wrongly assuming normality of the variables of interest and ignoring updating of the estimates of the parameters appearing in the statistical model. We show that both kinds of error may lead to large underestimations of the risk and, therefore, of the economic capital for reserving risk. These findings seem particularly important in a regulatory perspective.</abstract><cop>Northridge</cop><pub>Western Risk and Insurance Association</pub><tpages>27</tpages></addata></record> |
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| identifier | ISSN: 1531-6076 |
| ispartof | Journal of insurance issues, 2015-10, Vol.38 (2), p.157-183 |
| issn | 1531-6076 2332-4244 |
| language | eng |
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| source | EBSCOhost Business Source Complete; Jstor Complete Legacy |
| subjects | Accidents Capital Consistent estimators Estimation methods Estimators Insurance regulation Insurance risk Life insurance Maximum likelihood estimation Parametric models Risk management Solvency Statistical methods Statistical variance Studies |
| title | Evaluating Reserve Risk in a Regulatory Perspective |
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