Individual loss reserving using paid–incurred data
This paper develops a stochastic model for individual claims reserving using observed data on claim payments as well as incurred losses. We extend the approach of Pigeon et al. (2013), designed for payments only, towards the inclusion of incurred losses. We call the new technique the individual Paid...
Gespeichert in:
| Veröffentlicht in: | Insurance, mathematics & economics mathematics & economics, 2014-09, Vol.58, p.121-131 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 131 |
|---|---|
| container_issue | |
| container_start_page | 121 |
| container_title | Insurance, mathematics & economics |
| container_volume | 58 |
| creator | Pigeon, Mathieu Antonio, Katrien Denuit, Michel |
| description | This paper develops a stochastic model for individual claims reserving using observed data on claim payments as well as incurred losses. We extend the approach of Pigeon et al. (2013), designed for payments only, towards the inclusion of incurred losses. We call the new technique the individual Paid and Incurred Chain (iPIC) reserving method. Analytic expressions are derived for the expected ultimate losses, given observed development patterns. The usefulness of this new model is illustrated with a portfolio of general liability insurance policies. For the case study developed in this paper, detailed comparisons with existing approaches reveal that iPIC method performs well and produces more accurate predictions. |
| doi_str_mv | 10.1016/j.insmatheco.2014.06.012 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1639481378</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0167668714000845</els_id><sourcerecordid>1639481378</sourcerecordid><originalsourceid>FETCH-LOGICAL-c493t-1dcb44899e1b7925dd485a1cc402a0bb863143e4efbea95eb674f8b2f0a5a9513</originalsourceid><addsrcrecordid>eNqFkM1KxDAUhYMoOI6-Q8GNm9bcJk2TpQ7-wYAbXYc0udUMnXZM2gF3voNv6JOYYQTBjZt7ufCdwz2HkAxoARTE5arwfVyb8RXtUJQUeEFFQaE8IDOQNcsrValDMktonQsh62NyEuOKUgpK1DPCH3rnt95Npsu6IcYsYMSw9f1LNsXd3Bjvvj4-fW-nENBlzozmlBy1pot49rPn5Pn25mlxny8f7x4WV8vccsXGHJxtOJdKITS1KivnuKwMWMtpaWjTSMGAM-TYNmhUhY2oeSubsqWmSjewObnY-27C8DZhHPXaR4tdZ3ocpqhBMMUlsFom9PwPuhqm0KfvNFSC1QllKlFyT9mQsgZs9Sb4tQnvGqje1alX-rdOvatTU6FTnUl6vZdiCrz1GHS0HnuLzge0o3aD_9_kG0FMg8I</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1563716339</pqid></control><display><type>article</type><title>Individual loss reserving using paid–incurred data</title><source>Elsevier ScienceDirect Journals</source><creator>Pigeon, Mathieu ; Antonio, Katrien ; Denuit, Michel</creator><creatorcontrib>Pigeon, Mathieu ; Antonio, Katrien ; Denuit, Michel</creatorcontrib><description>This paper develops a stochastic model for individual claims reserving using observed data on claim payments as well as incurred losses. We extend the approach of Pigeon et al. (2013), designed for payments only, towards the inclusion of incurred losses. We call the new technique the individual Paid and Incurred Chain (iPIC) reserving method. Analytic expressions are derived for the expected ultimate losses, given observed development patterns. The usefulness of this new model is illustrated with a portfolio of general liability insurance policies. For the case study developed in this paper, detailed comparisons with existing approaches reveal that iPIC method performs well and produces more accurate predictions.</description><identifier>ISSN: 0167-6687</identifier><identifier>EISSN: 1873-5959</identifier><identifier>DOI: 10.1016/j.insmatheco.2014.06.012</identifier><identifier>CODEN: IMECDX</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Analytical philosophy ; Case studies ; Chain-Ladder ; Development strategies ; General insurance ; Insurance ; Insurance claims ; Insurance policies ; Insured losses ; Liability insurance ; Multivariate Skew Normal distribution ; Payments ; Prediction ; Stochastic loss reserving ; Stochastic models ; Studies</subject><ispartof>Insurance, mathematics & economics, 2014-09, Vol.58, p.121-131</ispartof><rights>2014 Elsevier B.V.</rights><rights>Copyright Elsevier Sequoia S.A. Sep 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c493t-1dcb44899e1b7925dd485a1cc402a0bb863143e4efbea95eb674f8b2f0a5a9513</citedby><cites>FETCH-LOGICAL-c493t-1dcb44899e1b7925dd485a1cc402a0bb863143e4efbea95eb674f8b2f0a5a9513</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0167668714000845$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,65309</link.rule.ids></links><search><creatorcontrib>Pigeon, Mathieu</creatorcontrib><creatorcontrib>Antonio, Katrien</creatorcontrib><creatorcontrib>Denuit, Michel</creatorcontrib><title>Individual loss reserving using paid–incurred data</title><title>Insurance, mathematics & economics</title><description>This paper develops a stochastic model for individual claims reserving using observed data on claim payments as well as incurred losses. We extend the approach of Pigeon et al. (2013), designed for payments only, towards the inclusion of incurred losses. We call the new technique the individual Paid and Incurred Chain (iPIC) reserving method. Analytic expressions are derived for the expected ultimate losses, given observed development patterns. The usefulness of this new model is illustrated with a portfolio of general liability insurance policies. For the case study developed in this paper, detailed comparisons with existing approaches reveal that iPIC method performs well and produces more accurate predictions.</description><subject>Analytical philosophy</subject><subject>Case studies</subject><subject>Chain-Ladder</subject><subject>Development strategies</subject><subject>General insurance</subject><subject>Insurance</subject><subject>Insurance claims</subject><subject>Insurance policies</subject><subject>Insured losses</subject><subject>Liability insurance</subject><subject>Multivariate Skew Normal distribution</subject><subject>Payments</subject><subject>Prediction</subject><subject>Stochastic loss reserving</subject><subject>Stochastic models</subject><subject>Studies</subject><issn>0167-6687</issn><issn>1873-5959</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqFkM1KxDAUhYMoOI6-Q8GNm9bcJk2TpQ7-wYAbXYc0udUMnXZM2gF3voNv6JOYYQTBjZt7ufCdwz2HkAxoARTE5arwfVyb8RXtUJQUeEFFQaE8IDOQNcsrValDMktonQsh62NyEuOKUgpK1DPCH3rnt95Npsu6IcYsYMSw9f1LNsXd3Bjvvj4-fW-nENBlzozmlBy1pot49rPn5Pn25mlxny8f7x4WV8vccsXGHJxtOJdKITS1KivnuKwMWMtpaWjTSMGAM-TYNmhUhY2oeSubsqWmSjewObnY-27C8DZhHPXaR4tdZ3ocpqhBMMUlsFom9PwPuhqm0KfvNFSC1QllKlFyT9mQsgZs9Sb4tQnvGqje1alX-rdOvatTU6FTnUl6vZdiCrz1GHS0HnuLzge0o3aD_9_kG0FMg8I</recordid><startdate>20140901</startdate><enddate>20140901</enddate><creator>Pigeon, Mathieu</creator><creator>Antonio, Katrien</creator><creator>Denuit, Michel</creator><general>Elsevier B.V</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><scope>JQ2</scope></search><sort><creationdate>20140901</creationdate><title>Individual loss reserving using paid–incurred data</title><author>Pigeon, Mathieu ; Antonio, Katrien ; Denuit, Michel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c493t-1dcb44899e1b7925dd485a1cc402a0bb863143e4efbea95eb674f8b2f0a5a9513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Analytical philosophy</topic><topic>Case studies</topic><topic>Chain-Ladder</topic><topic>Development strategies</topic><topic>General insurance</topic><topic>Insurance</topic><topic>Insurance claims</topic><topic>Insurance policies</topic><topic>Insured losses</topic><topic>Liability insurance</topic><topic>Multivariate Skew Normal distribution</topic><topic>Payments</topic><topic>Prediction</topic><topic>Stochastic loss reserving</topic><topic>Stochastic models</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pigeon, Mathieu</creatorcontrib><creatorcontrib>Antonio, Katrien</creatorcontrib><creatorcontrib>Denuit, Michel</creatorcontrib><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Computer Science Collection</collection><jtitle>Insurance, mathematics & economics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pigeon, Mathieu</au><au>Antonio, Katrien</au><au>Denuit, Michel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Individual loss reserving using paid–incurred data</atitle><jtitle>Insurance, mathematics & economics</jtitle><date>2014-09-01</date><risdate>2014</risdate><volume>58</volume><spage>121</spage><epage>131</epage><pages>121-131</pages><issn>0167-6687</issn><eissn>1873-5959</eissn><coden>IMECDX</coden><abstract>This paper develops a stochastic model for individual claims reserving using observed data on claim payments as well as incurred losses. We extend the approach of Pigeon et al. (2013), designed for payments only, towards the inclusion of incurred losses. We call the new technique the individual Paid and Incurred Chain (iPIC) reserving method. Analytic expressions are derived for the expected ultimate losses, given observed development patterns. The usefulness of this new model is illustrated with a portfolio of general liability insurance policies. For the case study developed in this paper, detailed comparisons with existing approaches reveal that iPIC method performs well and produces more accurate predictions.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.insmatheco.2014.06.012</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0167-6687 |
| ispartof | Insurance, mathematics & economics, 2014-09, Vol.58, p.121-131 |
| issn | 0167-6687 1873-5959 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1639481378 |
| source | Elsevier ScienceDirect Journals |
| subjects | Analytical philosophy Case studies Chain-Ladder Development strategies General insurance Insurance Insurance claims Insurance policies Insured losses Liability insurance Multivariate Skew Normal distribution Payments Prediction Stochastic loss reserving Stochastic models Studies |
| title | Individual loss reserving using paid–incurred data |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T22%3A33%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Individual%20loss%20reserving%20using%20paid%E2%80%93incurred%20data&rft.jtitle=Insurance,%20mathematics%20&%20economics&rft.au=Pigeon,%20Mathieu&rft.date=2014-09-01&rft.volume=58&rft.spage=121&rft.epage=131&rft.pages=121-131&rft.issn=0167-6687&rft.eissn=1873-5959&rft.coden=IMECDX&rft_id=info:doi/10.1016/j.insmatheco.2014.06.012&rft_dat=%3Cproquest_cross%3E1639481378%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1563716339&rft_id=info:pmid/&rft_els_id=S0167668714000845&rfr_iscdi=true |