{"id":"https://openalex.org/W4408789300","doi":"https://doi.org/10.1109/icecet63943.2025.11472238","title":"Artificial Intelligence-Based Strategies for Improving Customer Retention and Satisfaction in the Insurance Industry","display_name":"Artificial Intelligence-Based Strategies for Improving Customer Retention and Satisfaction in the Insurance Industry","publication_year":2025,"publication_date":"2025-03-24","ids":{"openalex":"https://openalex.org/W4408789300","doi":"https://doi.org/10.1109/icecet63943.2025.11472238"},"language":"en","primary_location":{"id":"doi:10.1109/icecet63943.2025.11472238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecet63943.2025.11472238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.174285150.03727082","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109004091","display_name":"Mahender Singh","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mahender Singh","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5109004091"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08374491,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12394","display_name":"Insurance and Financial Risk Management","score":0.9771999716758728,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12394","display_name":"Insurance and Financial Risk Management","score":0.9771999716758728,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14260","display_name":"Impact of AI and Big Data on Business and Society","score":0.926800012588501,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/customer-satisfaction","display_name":"Customer satisfaction","score":0.6786514520645142},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.6620607376098633},{"id":"https://openalex.org/keywords/customer-retention","display_name":"Customer retention","score":0.5839333534240723},{"id":"https://openalex.org/keywords/insurance-industry","display_name":"Insurance industry","score":0.5545173287391663},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.49752572178840637},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.3702963590621948},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.3369073271751404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2675860524177551},{"id":"https://openalex.org/keywords/actuarial-science","display_name":"Actuarial science","score":0.24450445175170898},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17734327912330627},{"id":"https://openalex.org/keywords/service-quality","display_name":"Service quality","score":0.14083561301231384}],"concepts":[{"id":"https://openalex.org/C191511416","wikidata":"https://www.wikidata.org/wiki/Q999278","display_name":"Customer satisfaction","level":2,"score":0.6786514520645142},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.6620607376098633},{"id":"https://openalex.org/C101276457","wikidata":"https://www.wikidata.org/wiki/Q5196474","display_name":"Customer retention","level":4,"score":0.5839333534240723},{"id":"https://openalex.org/C2984333267","wikidata":"https://www.wikidata.org/wiki/Q43183","display_name":"Insurance industry","level":2,"score":0.5545173287391663},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.49752572178840637},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3702963590621948},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.3369073271751404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2675860524177551},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.24450445175170898},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17734327912330627},{"id":"https://openalex.org/C140781008","wikidata":"https://www.wikidata.org/wiki/Q1221081","display_name":"Service quality","level":3,"score":0.14083561301231384},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icecet63943.2025.11472238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecet63943.2025.11472238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET)","raw_type":"proceedings-article"},{"id":"doi:10.36227/techrxiv.174285150.03727082/v1","is_oa":true,"landing_page_url":"https://doi.org/10.36227/techrxiv.174285150.03727082/v1","pdf_url":"https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.174285150.03727082","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Techrxiv","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.36227/techrxiv.174285150.03727082/v1","is_oa":true,"landing_page_url":"https://doi.org/10.36227/techrxiv.174285150.03727082/v1","pdf_url":"https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.174285150.03727082","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Techrxiv","raw_type":"posted-content"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.5,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408789300.pdf","grobid_xml":"https://content.openalex.org/works/W4408789300.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3091493342","https://openalex.org/W3015810715","https://openalex.org/W2357931527","https://openalex.org/W2152253706","https://openalex.org/W72876739","https://openalex.org/W2370799454","https://openalex.org/W2595990749","https://openalex.org/W4394063813","https://openalex.org/W2992905510","https://openalex.org/W3197768229"],"abstract_inverted_index":{"A":[0],"major":[1],"problem":[2],"in":[3,29,72,153,174],"many":[4],"sectors,":[5],"including":[6],"insurance,":[7],"is":[8,24,64,87],"customer":[9,68,183],"retention.":[10],"Because":[11],"insurance":[12,22,61,74,171],"contracts":[13],"are":[14,39,52],"often":[15],"renewed":[16],"annually,":[17],"keeping":[18],"consumers":[19,50],"inside":[20],"the":[21,42,49,56,73,88,146,160,168],"business":[23],"much":[25],"more":[26],"difficult":[27],"than":[28],"any":[30],"other":[31],"sector.":[32],"The":[33,76,93],"primary":[34],"goals":[35],"of":[36,78,90,132,137,162,170],"this":[37,91],"study":[38,94],"to":[40,46,81],"identify":[41,48],"risk":[43,178],"variables":[44],"linked":[45],"churn,":[47],"who":[51],"leaving,":[53],"and":[54,70,96,101,115,134,141,182,192],"predict":[55],"period":[57],"till":[58],"churn.":[59],"Accurate":[60],"premium":[62,83],"prediction":[63,85,155],"crucial":[65],"for":[66,166,196],"optimizing":[67],"retention":[69],"satisfaction":[71],"industry.":[75],"use":[77],"ML":[79,164],"models":[80,108,191],"improve":[82,177],"price":[84],"accuracy":[86],"focus":[89],"research.":[92],"implements":[95],"compares":[97],"Random":[98],"Forest":[99],"(RF)":[100],"Gradient":[102,117],"Boosting":[103,118],"Regression":[104,113],"(GBR)":[105],"with":[106],"baseline":[107],"such":[109],"as":[110],"Support":[111],"Vector":[112],"(SVR)":[114],"Extreme":[116],"(XGB).":[119],"Experimental":[120],"results":[121,158],"demonstrate":[122],"that":[123],"GBR":[124],"achieved":[125],"superior":[126],"predictive":[127],"performance,":[128],"attaining":[129],"an":[130,135],"R\u00b2":[131],"0.8652":[133],"RMSE":[136,148],"0.3839,":[138],"outperforming":[139],"RF":[140],"SVR.":[142],"Additionally,":[143],"XGB":[144],"exhibited":[145],"lowest":[147],"(0.2231),":[149],"highlighting":[150],"its":[151],"effectiveness":[152],"minimizing":[154],"errors.":[156],"These":[157],"highlight":[159],"promise":[161],"cutting-edge":[163],"methods":[165],"enhancing":[167],"forecasting":[169],"premiums,":[172],"which":[173],"turn":[175],"might":[176],"assessment,":[179],"pricing":[180],"tactics,":[181],"satisfaction.":[184],"Future":[185],"research":[186],"will":[187],"explore":[188],"deep":[189],"learning":[190],"real-time":[193],"data":[194],"integration":[195],"further":[197],"enhancement.":[198]},"counts_by_year":[],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}