{"id":"https://openalex.org/W7152935286","doi":null,"title":"Performance and fairness of machine learning modelling for general insurance pricing","display_name":"Performance and fairness of machine learning modelling for general insurance pricing","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W7152935286"},"language":"en","primary_location":{"id":"pmh:oai:cora.ucc.ie:10468/17992","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/10468/17992","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Doctoral thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/10468/17992","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040170861","display_name":"Tarun Israni","orcid":"https://orcid.org/0000-0003-2214-6396","observed_orcids":["https://orcid.org/0000-0003-2214-6396"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Israni, Tarun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5040170861"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12394","display_name":"Insurance and Financial Risk Management","score":0.5015000104904175,"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":0.5015000104904175,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.1736000031232834,"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/T11720","display_name":"Probability and Risk Models","score":0.05649999901652336,"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/price-fairness","display_name":"price fairness","score":0.8379999995231628},{"id":"https://openalex.org/keywords/machine-learning","display_name":"machine learning","score":0.7670000195503235},{"id":"https://openalex.org/keywords/generalized-linear-models","display_name":"generalized linear models","score":0.9390000104904175},{"id":"https://openalex.org/keywords/tree-based-ensemble-models","display_name":"tree-based ensemble models","score":0.9810000061988831},{"id":"https://openalex.org/keywords/poisson-gamma-model","display_name":"Poisson-gamma model","score":0.7630000114440918},{"id":"https://openalex.org/keywords/demographic-parity","display_name":"demographic parity","score":0.9089999794960022},{"id":"https://openalex.org/keywords/model-calibration","display_name":"model calibration","score":0.7760000228881836},{"id":"https://openalex.org/keywords/auto-insurance","display_name":"automobile insurance","score":0.8119999766349792},{"id":"https://openalex.org/keywords/third-party-liability","display_name":"third-party liability","score":0.8569999933242798},{"id":"https://openalex.org/keywords/central-bank-of-ireland","display_name":"Central Bank of Ireland","score":0.5920000076293945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6000999808311462},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5598999857902527},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.49799999594688416},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.45190000534057617},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.41339999437332153},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37459999322891235},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C68799949","wikidata":"https://www.wikidata.org/wiki/Q977871","display_name":"Insurance policy","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C2777617010","wikidata":"https://www.wikidata.org/wiki/Q18957","display_name":"Mainstream","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.33489999175071716},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.33320000767707825},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3068000078201294},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3037000000476837},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C41587187","wikidata":"https://www.wikidata.org/wiki/Q1501882","display_name":"Generalized linear model","level":2,"score":0.2619999945163727}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:cora.ucc.ie:10468/17992","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/10468/17992","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Doctoral thesis"}],"best_oa_location":{"id":"pmh:oai:cora.ucc.ie:10468/17992","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/10468/17992","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Doctoral thesis"},"sustainable_development_goals":[{"score":0.7578999996185303,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7126108513","https://openalex.org/W7117979413","https://openalex.org/W4379928685","https://openalex.org/W7154608141","https://openalex.org/W2905123776","https://openalex.org/W7008604353","https://openalex.org/W7125469445","https://openalex.org/W4226133645","https://openalex.org/W4205697237","https://openalex.org/W4393357377"],"abstract_inverted_index":{"An":[0],"increasing":[1],"number":[2],"of":[3,9,48,73,125,128,160,181,211,226,241,243,256,266],"reports":[4],"underscore":[5],"the":[6,20,46,74,157,195,200,209,239,253,264],"promising":[7],"potential":[8,210],"machine":[10],"learning":[11],"(ML)":[12],"methodologies":[13],"for":[14,61,163,204,281],"general":[15,282],"insurance":[16,62,174,283],"pricing":[17,37,54,99,260],"compared":[18],"to":[19,141,219,230,245,262],"conventional":[21],"generalised":[22],"linear":[23,86],"model":[24,81,193],"(GLM).":[25],"This":[26,120],"shift":[27],"towards":[28],"ML":[29,192,212,274],"is":[30,58,291],"coupled":[31],"with":[32,139,177],"a":[33,59,70,79,146,178,214,234],"growing":[34],"emphasis":[35],"on":[36,156,170,238,271],"fairness":[38,57,129,152,232,289,295],"by":[39],"national":[40],"and":[41,56,64,88,102,118,136,151,186,216,269,288,294],"international":[42],"regulatory":[43,65],"institutions.":[44],"However,":[45,285],"scarcity":[47],"comprehensive":[49,71,185],"studies":[50],"that":[51],"assess":[52],"both":[53],"accuracy":[55,287],"challenge":[60],"companies":[63],"bodies":[66],"alike.":[67],"We":[68,92],"propose":[69],"study":[72,121,249],"GLM":[75,201],"-":[76,82,130,138],"acting":[77],"as":[78,108,213],"benchmark":[80],"against":[83],"mainstream":[84],"regularised":[85],"models":[87,95,167,275],"tree-based":[89],"ensemble":[90],"models.":[91],"evaluate":[93],"these":[94],"in":[96,299],"two":[97,171],"common":[98],"frameworks":[100],"(Poisson-gamma":[101],"Tweedie),":[103],"considering":[104],"key":[105],"criteria":[106],"such":[107],"estimation":[109],"bias,":[110],"deviance,":[111],"risk":[112],"classification,":[113],"competitiveness,":[114],"loss":[115],"ratios,":[116],"discrimination,":[117],"fairness.":[119],"includes":[122],"an":[123],"evaluation":[124],"three":[126],"definitions":[127],"demographic":[131],"parity,":[132],"actuarial":[133],"group":[134],"fairness,":[135],"calibration":[137],"respect":[140],"protected":[142],"policyholder":[143],"information":[144],"at":[145],"population":[147],"level.":[148],"Pricing":[149],"performance":[150],"are":[153,168],"assessed":[154,169],"simultaneously":[155,290],"same":[158],"samples":[159],"premium":[161],"estimates":[162],"each":[164,176],"model.":[165],"The":[166,206,223,248],"open-access":[172],"motor":[173],"datasets,":[175],"different":[179,235],"type":[180],"cover":[182],"(namely":[183],"fully":[184],"third-party":[187],"liability).":[188],"While":[189],"no":[190],"single":[191],"outperformed":[194,276],"others":[196],"across":[197],"all":[198],"metrics,":[199],"significantly":[202],"underperformed":[203],"most.":[205],"results":[207],"demonstrate":[208],"realistic":[215],"reasonable":[217],"alternative":[218],"current":[220],"industry":[221],"practices.":[222],"last":[224],"chapter":[225],"this":[227],"thesis":[228],"proposes":[229],"consider":[231],"under":[233],"light,":[236],"focusing":[237],"analysis":[240],"ratios":[242],"actual":[244],"technical":[246],"premiums.":[247],"incorporates":[250],"metrics":[251,280],"from":[252],"Central":[254],"Bank":[255],"Ireland":[257],"(CBI)":[258],"differential":[259],"review,":[261],"examine":[263],"impact":[265],"gender,":[267],"tenure,":[268],"age":[270],"pricing.":[272,284],"Overall,":[273],"GLMs":[277],"over":[278],"most":[279],"achieving":[286],"not":[292],"straightforward,":[293],"may":[296],"be":[297],"understood":[298],"various":[300],"ways.":[301]},"counts_by_year":[],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2026-04-10T00:00:00"}
