{"id":"https://openalex.org/W4415918514","doi":"https://doi.org/10.1007/s44163-025-00574-5","title":"Generative hybrid models for fraud detection in auto insurance with a comparative analysis of VAE, GAN, and diffusion approaches","display_name":"Generative hybrid models for fraud detection in auto insurance with a comparative analysis of VAE, GAN, and diffusion approaches","publication_year":2025,"publication_date":"2025-11-05","ids":{"openalex":"https://openalex.org/W4415918514","doi":"https://doi.org/10.1007/s44163-025-00574-5"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00574-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00574-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00574-5.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00574-5.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092339989","display_name":"Chadia Bekkaye","orcid":"https://orcid.org/0009-0009-9610-8000"},"institutions":[{"id":"https://openalex.org/I99297268","display_name":"University of Hassan II Casablanca","ror":"https://ror.org/001q4kn48","country_code":"MA","type":"education","lineage":["https://openalex.org/I99297268"]}],"countries":["MA"],"is_corresponding":true,"raw_author_name":"Chadia Bekkaye","raw_affiliation_strings":["MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco"],"affiliations":[{"raw_affiliation_string":"MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco","institution_ids":["https://openalex.org/I99297268"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092361377","display_name":"Hassan Oukhouya","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108110","display_name":"Mohamed I University","ror":"https://ror.org/01ejxf797","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210108110"]},{"id":"https://openalex.org/I76129166","display_name":"Premier University","ror":"https://ror.org/02j96nm37","country_code":"BD","type":"education","lineage":["https://openalex.org/I76129166"]},{"id":"https://openalex.org/I99297268","display_name":"University of Hassan II Casablanca","ror":"https://ror.org/001q4kn48","country_code":"MA","type":"education","lineage":["https://openalex.org/I99297268"]}],"countries":["BD","MA"],"is_corresponding":false,"raw_author_name":"Hassan Oukhouya","raw_affiliation_strings":["LaMSD, Team of MSASE, Department of Economics, Mohammed First University, BV Mohammed VI, B.P. 724, 60000, Oujda, Morocco","MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco"],"affiliations":[{"raw_affiliation_string":"LaMSD, Team of MSASE, Department of Economics, Mohammed First University, BV Mohammed VI, B.P. 724, 60000, Oujda, Morocco","institution_ids":["https://openalex.org/I4210108110","https://openalex.org/I76129166"]},{"raw_affiliation_string":"MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco","institution_ids":["https://openalex.org/I99297268"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052647720","display_name":"Tarek Zari","orcid":"https://orcid.org/0000-0002-3549-128X"},"institutions":[{"id":"https://openalex.org/I99297268","display_name":"University of Hassan II Casablanca","ror":"https://ror.org/001q4kn48","country_code":"MA","type":"education","lineage":["https://openalex.org/I99297268"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Tarek Zari","raw_affiliation_strings":["MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco"],"affiliations":[{"raw_affiliation_string":"MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco","institution_ids":["https://openalex.org/I99297268"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093614389","display_name":"Raby Guerbaz","orcid":"https://orcid.org/0009-0009-7303-6008"},"institutions":[{"id":"https://openalex.org/I99297268","display_name":"University of Hassan II Casablanca","ror":"https://ror.org/001q4kn48","country_code":"MA","type":"education","lineage":["https://openalex.org/I99297268"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Raby Guerbaz","raw_affiliation_strings":["MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco"],"affiliations":[{"raw_affiliation_string":"MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco","institution_ids":["https://openalex.org/I99297268"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5119692834","display_name":"Hicham El Bouanani","orcid":"https://orcid.org/0009-0002-5211-9831"},"institutions":[{"id":"https://openalex.org/I99297268","display_name":"University of Hassan II Casablanca","ror":"https://ror.org/001q4kn48","country_code":"MA","type":"education","lineage":["https://openalex.org/I99297268"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Hicham El Bouanani","raw_affiliation_strings":["MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco"],"affiliations":[{"raw_affiliation_string":"MAEGE Laboratory, Department of Statistics and Applied Mathematics, Hassan II University, BP 2634,  Route des Chaux et Ciments Beausite, 20254, Casablanca, Morocco","institution_ids":["https://openalex.org/I99297268"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5092339989"],"corresponding_institution_ids":["https://openalex.org/I99297268"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17247222,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9477999806404114,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9477999806404114,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.006300000008195639,"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.004900000058114529,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5952000021934509},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.551800012588501},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5461999773979187},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4884999990463257},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.47540000081062317},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.44110000133514404},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.41749998927116394},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4047999978065491},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.39739999175071716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.680400013923645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6044999957084656},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5952000021934509},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5831999778747559},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.551800012588501},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5461999773979187},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4884999990463257},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48649999499320984},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.47540000081062317},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.44110000133514404},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.33820000290870667},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.3379000127315521},{"id":"https://openalex.org/C162040801","wikidata":"https://www.wikidata.org/wiki/Q799897","display_name":"Bootstrap aggregating","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C2777317252","wikidata":"https://www.wikidata.org/wiki/Q18393516","display_name":"Rare events","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.26460000872612}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00574-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00574-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00574-5.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a1e8845110324ee588f20f091b21a768","is_oa":true,"landing_page_url":"https://doaj.org/article/a1e8845110324ee588f20f091b21a768","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-23 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00574-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00574-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00574-5.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415918514.pdf","grobid_xml":"https://content.openalex.org/works/W4415918514.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1003236940","https://openalex.org/W2040290480","https://openalex.org/W2045326521","https://openalex.org/W2073241381","https://openalex.org/W2104933073","https://openalex.org/W2125820445","https://openalex.org/W2148143831","https://openalex.org/W2158698691","https://openalex.org/W2167488165","https://openalex.org/W2170505850","https://openalex.org/W2170849156","https://openalex.org/W2295598076","https://openalex.org/W2296719434","https://openalex.org/W2565336787","https://openalex.org/W2769984510","https://openalex.org/W2911964244","https://openalex.org/W3014078607","https://openalex.org/W3097282267","https://openalex.org/W3106889297","https://openalex.org/W3111180383","https://openalex.org/W3120065861","https://openalex.org/W3183560208","https://openalex.org/W3197173171","https://openalex.org/W4212841871","https://openalex.org/W4224271690","https://openalex.org/W4243367342","https://openalex.org/W4292133399","https://openalex.org/W4292691288","https://openalex.org/W4379141187","https://openalex.org/W4386028577","https://openalex.org/W4386136961","https://openalex.org/W4388656584","https://openalex.org/W4390906464","https://openalex.org/W4392208038","https://openalex.org/W4399159797","https://openalex.org/W4400106382","https://openalex.org/W4400131777","https://openalex.org/W4402163891","https://openalex.org/W4402891761","https://openalex.org/W4406808220","https://openalex.org/W4408473948","https://openalex.org/W4408477201","https://openalex.org/W4411410040","https://openalex.org/W4414400953"],"related_works":[],"abstract_inverted_index":{"Fraud":[0],"claim":[1],"detection":[2,98,206],"in":[3,204,214],"auto":[4],"insurance":[5,217],"remains":[6],"a":[7,54,185],"vital":[8],"yet":[9],"complex":[10],"challenge,":[11],"mainly":[12],"due":[13],"to":[14,105],"imbalanced":[15],"data":[16],"sets,":[17],"non-linear":[18],"feature":[19],"interactions,":[20],"and":[21,43,69,85,99,103,116,130,133,139,158,166,169,174,193,207],"the":[22,198,209],"necessity":[23],"for":[24,96,211],"explicable":[25],"predictions.":[26],"While":[27],"traditional":[28],"Machine":[29],"Learning":[30],"(ML)":[31],"approaches":[32],"show":[33],"promise,":[34],"they":[35],"frequently":[36],"struggle":[37],"from":[38],"poor":[39],"generalization,":[40],"limited":[41],"interpretability,":[42],"inadequate":[44],"treatment":[45],"of":[46,75,200],"rare":[47],"fraudulent":[48],"cases.":[49],"The":[50,142],"present":[51],"paper":[52],"proposes":[53],"new":[55],"hybrid":[56,112,202],"approach":[57],"involving":[58],"generative":[59],"models":[60,203],"\u2014namely":[61],"Variational":[62],"AutoEncoders":[63],"(VAEs),":[64],"Generative":[65],"Adversarial":[66],"Networks":[67],"(GANs),":[68],"Diffusion":[70],"Models":[71],"(DMs)\u2014with":[72],"an":[73],"ensemble":[74],"classifiers":[76],"including":[77],"eXtreme":[78],"Gradient":[79,87],"Boosting":[80,88],"(XGBoost),":[81],"Random":[82],"Forest":[83,94],"(RF),":[84],"Light":[86,172],"(Light":[89],"GBM),":[90],"coupled":[91,163],"with":[92,164,171],"Isolation":[93],"(IF)":[95],"anomaly":[97],"oversampling-based":[100],"techniques":[101],"(SMOTE":[102],"ADASYN)":[104],"ameliorate":[106],"class":[107],"balance.":[108],"In":[109,181],"total,":[110],"18":[111],"combinations":[113],"were":[114],"developed":[115],"evaluated":[117],"across":[118],"classification":[119],"performance":[120],"(AUC-ROC,":[121],"Accuracy,":[122],"Precision,":[123],"Recall,":[124],"F1-score),":[125],"probabilistic":[126],"calibration":[127],"(Brier":[128],"Score":[129],"Log":[131],"loss),":[132],"stochastic":[134],"stability":[135],"(Monte":[136],"Carlo":[137],"Variance":[138],"Bootstrap":[140],"Variance).":[141],"experimental":[143],"findings\u2014backed":[144],"up":[145],"by":[146],"graphical":[147],"analysis":[148],"based":[149],"on":[150],"radar":[151],"plots,":[152],"ROC":[153],"curves,":[154],"3D":[155],"metric":[156],"visualization,":[157],"SHAP":[159],"explainability\u2014confirm":[160],"that":[161],"DM":[162,170],"XGBoost":[165],"SMOTE":[167,175],"(DM_XGBoost_SMOTE)":[168],"GBM":[173],"(DM_Light":[176],"GBM_SMOTE)":[177],"outperform":[178],"alternative":[179],"combinations.":[180],"particular,":[182],"DM_XGBoost_SMOTE":[183],"achieves":[184],"well":[186],"balanced":[187],"compromise":[188],"between":[189],"accuracy,":[190],"confidence":[191],"calibration,":[192],"robustness.":[194],"This":[195],"work":[196],"underlines":[197],"efficiency":[199],"Diffusion-based":[201],"fraud":[205],"opens":[208],"way":[210],"their":[212],"implementation":[213],"high-risk,":[215],"real-world":[216],"environments.":[218]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-05T00:00:00"}
