{"id":"https://openalex.org/W4385488753","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191171","title":"Explainable exclusion in the life insurance using multi-label classifier","display_name":"Explainable exclusion in the life insurance using multi-label classifier","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385488753","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191171"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191171","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080247792","display_name":"Khanh V\u0103n Nguy\u1ec5n","orcid":"https://orcid.org/0000-0002-9769-9625"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Khanh Van Nguyen","raw_affiliation_strings":["School of Computer Science University of Technology Sydney,Sydney,Australia","School of Computer Science University of Technology Sydney, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science University of Technology Sydney,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"School of Computer Science University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088820799","display_name":"Md Rafiqul Islam","orcid":"https://orcid.org/0000-0001-7209-3881"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Md Rafiqul Islam","raw_affiliation_strings":["School of Computer Science University of Technology Sydney,Sydney,Australia","School of Computer Science University of Technology Sydney, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science University of Technology Sydney,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"School of Computer Science University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102878677","display_name":"Huan Huo","orcid":"https://orcid.org/0000-0003-2440-714X"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Huan Huo","raw_affiliation_strings":["School of Computer Science University of Technology Sydney,Sydney,Australia","School of Computer Science University of Technology Sydney, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science University of Technology Sydney,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"School of Computer Science University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043977984","display_name":"Peter Tilocca","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peter Tilocca","raw_affiliation_strings":["Life and Investments Zurich Financial Services,Sydney,Australia","Life and Investments Zurich Financial Services, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Life and Investments Zurich Financial Services,Sydney,Australia","institution_ids":[]},{"raw_affiliation_string":"Life and Investments Zurich Financial Services, Sydney, Australia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051512158","display_name":"Guandong Xu","orcid":"https://orcid.org/0000-0003-4493-6663"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guandong Xu","raw_affiliation_strings":["School of Computer Science University of Technology Sydney,Sydney,Australia","School of Computer Science University of Technology Sydney, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science University of Technology Sydney,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"School of Computer Science University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7506143450737},{"id":"https://openalex.org/keywords/underwriting","display_name":"Underwriting","score":0.7362918853759766},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.658626139163971},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.635909378528595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5923831462860107},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5496869087219238},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.540607213973999},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.539985179901123},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5333333611488342},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5130757093429565},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.41201186180114746},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3811475932598114},{"id":"https://openalex.org/keywords/actuarial-science","display_name":"Actuarial science","score":0.14834019541740417},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.0871298611164093}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7506143450737},{"id":"https://openalex.org/C26503482","wikidata":"https://www.wikidata.org/wiki/Q1898080","display_name":"Underwriting","level":2,"score":0.7362918853759766},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.658626139163971},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.635909378528595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5923831462860107},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5496869087219238},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.540607213973999},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.539985179901123},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5333333611488342},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5130757093429565},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.41201186180114746},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3811475932598114},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.14834019541740417},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0871298611164093}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191171","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191171","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.49000000953674316,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G1844203821","display_name":null,"funder_award_id":"DP22010371,LE220100078","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2012995268","https://openalex.org/W2128253527","https://openalex.org/W2370234760","https://openalex.org/W2586665457","https://openalex.org/W2602346576","https://openalex.org/W2657631929","https://openalex.org/W2803781591","https://openalex.org/W2958089299","https://openalex.org/W2962862931","https://openalex.org/W2991579958","https://openalex.org/W3021918275","https://openalex.org/W3088938881","https://openalex.org/W3097734923","https://openalex.org/W3112248285","https://openalex.org/W3112552342","https://openalex.org/W3128415798","https://openalex.org/W3138819813","https://openalex.org/W4283166416","https://openalex.org/W6678889254","https://openalex.org/W6733436168","https://openalex.org/W6737947904","https://openalex.org/W6839195704"],"related_works":["https://openalex.org/W4389954502","https://openalex.org/W2771255398","https://openalex.org/W2930428186","https://openalex.org/W3200027047","https://openalex.org/W4385770464","https://openalex.org/W3125536479","https://openalex.org/W4224262160","https://openalex.org/W3120363735","https://openalex.org/W4214820172","https://openalex.org/W2394323384"],"abstract_inverted_index":{"To":[0],"reduce":[1],"manual":[2],"tasks":[3,40],"and":[4,29,137,179,193,215],"to":[5,69,77,102],"minimise":[6],"the":[7,38,45,63,74,79,90,104,108,113,159,165,174,185,220,224,230,246],"risks":[8,46],"from":[9,112],"a":[10,47,51,56,124,199,242],"customer,":[11],"many":[12],"insurance":[13,53,167],"companies":[14,168],"have":[15,60,67],"applied":[16],"ar-tificial":[17],"intelligence":[18],"(AI)":[19],"solutions,":[20],"including,":[21],"but":[22],"not":[23],"limited":[24],"to,":[25],"machine":[26],"learning":[27,31],"(ML)":[28],"deep":[30],"(DL).":[32],"Exclusion":[33],"anal-ysis":[34],"is":[35],"one":[36,163],"of":[37,43,92,126,164,245],"primary":[39,64,100],"in":[41,106,169],"terms":[42],"minimising":[44],"customer":[48,114],"imposes":[49],"on":[50],"life":[52],"company.":[54],"Although":[55],"few":[57],"research":[58,72],"studies":[59],"made":[61],"this":[62,87,120],"focus,":[65],"they":[66],"yet":[68],"provide":[70],"explainable":[71,186,239],"for":[73,184,238],"exclusion":[75,93],"analysis":[76],"assist":[78,103],"underwriting":[80,109],"process":[81,91],"(UP)":[82],"using":[83,158],"ML/DL":[84],"methods.":[85],"Therefore,":[86],"paper":[88,205],"makes":[89],"classification,":[94],"along":[95],"with":[96,141,229],"its":[97,99],"explainability,":[98],"concentration":[101],"underwriters":[105],"understanding":[107],"data":[110,160],"taken":[111],"disclosure":[115],"information.":[116],"First,":[117],"we":[118,172],"explore":[119],"problem":[121],"by":[122,162,211],"applying":[123],"set":[125],"four":[127],"multi-label":[128],"classifiers":[129],"(named":[130,145],"binary":[131,225],"relevance,":[132],"classifier":[133,233],"chains,":[134],"label":[135],"powerset,":[136],"ensemble":[138],"learning)":[139],"blended":[140],"five":[142],"ML":[143,187],"techniques":[144],"multinomial":[146],"Naive":[147],"Bayes,":[148],"support":[149],"vector":[150],"classifier,":[151],"logistic":[152],"regression,":[153],"random":[154],"forest,":[155],"decision":[156,231],"tree),":[157],"provided":[161],"leading":[166],"Australia.":[170],"Then,":[171],"consider":[173],"best-performing":[175],"model's":[176],"classification":[177],"probability":[178],"feature":[180],"importance":[181],"as":[182,198],"input":[183],"system":[188],"-":[189,197],"Shapley":[190],"additive":[191],"explanations":[192],"introduced":[194],"explainability":[195],"outcome":[196],"quality":[200],"assurance":[201],"report":[202],"(QAR).":[203],"This":[204],"offers":[206],"an":[207],"extensive":[208],"empirical":[209],"evaluation":[210],"comparing":[212],"different":[213],"metrics":[214],"human":[216],"underwriters'":[217],"reviews.":[218],"Finally,":[219],"result":[221],"demonstrates":[222],"that":[223],"relevance":[226],"algorithm":[227],"combined":[228],"tree":[232],"outperforms":[234],"other":[235],"existing":[236],"methods":[237],"exclusion,":[240],"providing":[241],"better":[243],"overview":[244],"customer's":[247],"risk":[248],"profile.":[249]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}