Fuzzy logic in insurance
The insurance industry has numerous areas with potential applications for fuzzy logic (FL). These include classification, underwriting, projected liabilities, fuzzy future and present values, pricing, asset allocations and cash flows, and investment. Given this potential and the impetus on FL during...
Gespeichert in:
| Veröffentlicht in: | Insurance, mathematics & economics mathematics & economics, 2004-10, Vol.35 (2), p.399-424 |
|---|---|
| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 424 |
|---|---|
| container_issue | 2 |
| container_start_page | 399 |
| container_title | Insurance, mathematics & economics |
| container_volume | 35 |
| creator | Shapiro, Arnold F. |
| description | The insurance industry has numerous areas with potential applications for fuzzy logic (FL). These include classification, underwriting, projected liabilities, fuzzy future and present values, pricing, asset allocations and cash flows, and investment. Given this potential and the impetus on FL during the last decade, it is not surprising that a number of FL studies have focused on insurance applications. This article presents an overview of these studies. The specific purposes of the article are two-fold: first, to review FL applications in insurance so as to document the unique characteristics of insurance as an application area; and second, to document the extent to which FL technologies have been employed. |
| doi_str_mv | 10.1016/j.insmatheco.2004.07.010 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_37998281</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0167668704000903</els_id><sourcerecordid>37998281</sourcerecordid><originalsourceid>FETCH-LOGICAL-c472t-1ecf0c7badfd1e1104c5d6bb56668adcacee0123a76ad46580cfda1d9481e26a3</originalsourceid><addsrcrecordid>eNqFkL1PwzAQxS0EEqWwM1YMbAnnfNjJCBXlQ5VYYD659oW6apJiJ5Xavx6HIpBYkH1nS37v-fRjbMIh5sDFzSq2ja9VtyTdxglAFoOMgcMRG_FCplFe5uUxGwWpjIQo5Ck7834FALwUcsQuZ_1-v5us23erJ7YJ2_dONZrO2Uml1p4uvs8xe5vdv04fo_nLw9P0dh7pTCZdxElXoOVCmcpw4hwynRuxWOQifKaMVpoIeJIqKZTJRF6ArozipswKTolQ6ZhdH3I3rv3oyXdYW69pvVYNtb3HVJZlkRQ8CK_-CFdt75owGyZQcJmFFUTFQaRd672jCjfO1srtkAMOvHCFv7xw4IUgMfAK1ueD1dGG9I-PiAYmtcItpirNQ9uF-nKmyg7XUJvhrSwxSzJcdnUIuzuEUUC3teTQa0sBq7GOdIemtf9P9An7lpFA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>208174747</pqid></control><display><type>article</type><title>Fuzzy logic in insurance</title><source>RePEc</source><source>Elsevier ScienceDirect Journals Complete</source><creator>Shapiro, Arnold F.</creator><creatorcontrib>Shapiro, Arnold F.</creatorcontrib><description>The insurance industry has numerous areas with potential applications for fuzzy logic (FL). These include classification, underwriting, projected liabilities, fuzzy future and present values, pricing, asset allocations and cash flows, and investment. Given this potential and the impetus on FL during the last decade, it is not surprising that a number of FL studies have focused on insurance applications. This article presents an overview of these studies. The specific purposes of the article are two-fold: first, to review FL applications in insurance so as to document the unique characteristics of insurance as an application area; and second, to document the extent to which FL technologies have been employed.</description><identifier>ISSN: 0167-6687</identifier><identifier>EISSN: 1873-5959</identifier><identifier>DOI: 10.1016/j.insmatheco.2004.07.010</identifier><identifier>CODEN: IMECDX</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Actuarial ; Fuzzy clustering ; Fuzzy inference systems ; Fuzzy logic ; Fuzzy sets ; Insurance ; Insurance applications ; Insurance industry ; Mathematical methods ; Mathematics ; Risk theory ; Studies</subject><ispartof>Insurance, mathematics & economics, 2004-10, Vol.35 (2), p.399-424</ispartof><rights>2004 Elsevier B.V.</rights><rights>Copyright Elsevier Sequoia S.A. Oct 11, 2004</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c472t-1ecf0c7badfd1e1104c5d6bb56668adcacee0123a76ad46580cfda1d9481e26a3</citedby><cites>FETCH-LOGICAL-c472t-1ecf0c7badfd1e1104c5d6bb56668adcacee0123a76ad46580cfda1d9481e26a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0167668704000903$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,3994,27901,27902,65534</link.rule.ids><backlink>$$Uhttp://econpapers.repec.org/article/eeeinsuma/v_3a35_3ay_3a2004_3ai_3a2_3ap_3a399-424.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Shapiro, Arnold F.</creatorcontrib><title>Fuzzy logic in insurance</title><title>Insurance, mathematics & economics</title><description>The insurance industry has numerous areas with potential applications for fuzzy logic (FL). These include classification, underwriting, projected liabilities, fuzzy future and present values, pricing, asset allocations and cash flows, and investment. Given this potential and the impetus on FL during the last decade, it is not surprising that a number of FL studies have focused on insurance applications. This article presents an overview of these studies. The specific purposes of the article are two-fold: first, to review FL applications in insurance so as to document the unique characteristics of insurance as an application area; and second, to document the extent to which FL technologies have been employed.</description><subject>Actuarial</subject><subject>Fuzzy clustering</subject><subject>Fuzzy inference systems</subject><subject>Fuzzy logic</subject><subject>Fuzzy sets</subject><subject>Insurance</subject><subject>Insurance applications</subject><subject>Insurance industry</subject><subject>Mathematical methods</subject><subject>Mathematics</subject><subject>Risk theory</subject><subject>Studies</subject><issn>0167-6687</issn><issn>1873-5959</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNqFkL1PwzAQxS0EEqWwM1YMbAnnfNjJCBXlQ5VYYD659oW6apJiJ5Xavx6HIpBYkH1nS37v-fRjbMIh5sDFzSq2ja9VtyTdxglAFoOMgcMRG_FCplFe5uUxGwWpjIQo5Ck7834FALwUcsQuZ_1-v5us23erJ7YJ2_dONZrO2Uml1p4uvs8xe5vdv04fo_nLw9P0dh7pTCZdxElXoOVCmcpw4hwynRuxWOQifKaMVpoIeJIqKZTJRF6ArozipswKTolQ6ZhdH3I3rv3oyXdYW69pvVYNtb3HVJZlkRQ8CK_-CFdt75owGyZQcJmFFUTFQaRd672jCjfO1srtkAMOvHCFv7xw4IUgMfAK1ueD1dGG9I-PiAYmtcItpirNQ9uF-nKmyg7XUJvhrSwxSzJcdnUIuzuEUUC3teTQa0sBq7GOdIemtf9P9An7lpFA</recordid><startdate>20041011</startdate><enddate>20041011</enddate><creator>Shapiro, Arnold F.</creator><general>Elsevier B.V</general><general>Elsevier</general><general>Elsevier Sequoia S.A</general><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><scope>JQ2</scope></search><sort><creationdate>20041011</creationdate><title>Fuzzy logic in insurance</title><author>Shapiro, Arnold F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c472t-1ecf0c7badfd1e1104c5d6bb56668adcacee0123a76ad46580cfda1d9481e26a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Actuarial</topic><topic>Fuzzy clustering</topic><topic>Fuzzy inference systems</topic><topic>Fuzzy logic</topic><topic>Fuzzy sets</topic><topic>Insurance</topic><topic>Insurance applications</topic><topic>Insurance industry</topic><topic>Mathematical methods</topic><topic>Mathematics</topic><topic>Risk theory</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shapiro, Arnold F.</creatorcontrib><collection>RePEc IDEAS</collection><collection>RePEc</collection><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>Shapiro, Arnold F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy logic in insurance</atitle><jtitle>Insurance, mathematics & economics</jtitle><date>2004-10-11</date><risdate>2004</risdate><volume>35</volume><issue>2</issue><spage>399</spage><epage>424</epage><pages>399-424</pages><issn>0167-6687</issn><eissn>1873-5959</eissn><coden>IMECDX</coden><abstract>The insurance industry has numerous areas with potential applications for fuzzy logic (FL). These include classification, underwriting, projected liabilities, fuzzy future and present values, pricing, asset allocations and cash flows, and investment. Given this potential and the impetus on FL during the last decade, it is not surprising that a number of FL studies have focused on insurance applications. This article presents an overview of these studies. The specific purposes of the article are two-fold: first, to review FL applications in insurance so as to document the unique characteristics of insurance as an application area; and second, to document the extent to which FL technologies have been employed.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.insmatheco.2004.07.010</doi><tpages>26</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0167-6687 |
| ispartof | Insurance, mathematics & economics, 2004-10, Vol.35 (2), p.399-424 |
| issn | 0167-6687 1873-5959 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_37998281 |
| source | RePEc; Elsevier ScienceDirect Journals Complete |
| subjects | Actuarial Fuzzy clustering Fuzzy inference systems Fuzzy logic Fuzzy sets Insurance Insurance applications Insurance industry Mathematical methods Mathematics Risk theory Studies |
| title | Fuzzy logic in insurance |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-21T18%3A20%3A10IST&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=Fuzzy%20logic%20in%20insurance&rft.jtitle=Insurance,%20mathematics%20&%20economics&rft.au=Shapiro,%20Arnold%20F.&rft.date=2004-10-11&rft.volume=35&rft.issue=2&rft.spage=399&rft.epage=424&rft.pages=399-424&rft.issn=0167-6687&rft.eissn=1873-5959&rft.coden=IMECDX&rft_id=info:doi/10.1016/j.insmatheco.2004.07.010&rft_dat=%3Cproquest_cross%3E37998281%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=208174747&rft_id=info:pmid/&rft_els_id=S0167668704000903&rfr_iscdi=true |