{"id":"https://openalex.org/W7152638117","doi":"https://doi.org/10.1111/exsy.70256","title":"Imbalance\u2010Aware Credit Card Fraud Detection Using Multi\u2010Autoencoders and Generative Ensemble Learning","display_name":"Imbalance\u2010Aware Credit Card Fraud Detection Using Multi\u2010Autoencoders and Generative Ensemble Learning","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7152638117","doi":"https://doi.org/10.1111/exsy.70256"},"language":"en","primary_location":{"id":"doi:10.1111/exsy.70256","is_oa":true,"landing_page_url":"https://doi.org/10.1111/exsy.70256","pdf_url":null,"source":{"id":"https://openalex.org/S72232612","display_name":"Expert Systems","issn_l":"0266-4720","issn":["0266-4720","1468-0394"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1111/exsy.70256","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062128133","display_name":"Sultan H. Alharbi","orcid":"https://orcid.org/0000-0001-8146-8032"},"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"]},{"id":"https://openalex.org/I199693650","display_name":"Umm al-Qura University","ror":"https://ror.org/01xjqrm90","country_code":"SA","type":"education","lineage":["https://openalex.org/I199693650"]}],"countries":["AU","SA"],"is_corresponding":true,"raw_author_name":"Sultan Alharbi","raw_affiliation_strings":["Umm Al Qura University  Makkah Saudi Arabia","University of Technology Sydney  Sydney New South Wales Australia"],"raw_orcid":"https://orcid.org/0000-0001-8146-8032","affiliations":[{"raw_affiliation_string":"Umm Al Qura University  Makkah Saudi Arabia","institution_ids":["https://openalex.org/I199693650"]},{"raw_affiliation_string":"University of Technology Sydney  Sydney New South Wales Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003927827","display_name":"Khalid AlAhmadi","orcid":null},"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"]},{"id":"https://openalex.org/I185163786","display_name":"King Abdulaziz University","ror":"https://ror.org/02ma4wv74","country_code":"SA","type":"education","lineage":["https://openalex.org/I185163786"]}],"countries":["AU","SA"],"is_corresponding":false,"raw_author_name":"Khalid Alahmadi","raw_affiliation_strings":["King Abdulaziz University  Jeddah Saudi Arabia","University of Technology Sydney  Sydney New South Wales Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King Abdulaziz University  Jeddah Saudi Arabia","institution_ids":["https://openalex.org/I185163786"]},{"raw_affiliation_string":"University of Technology Sydney  Sydney New South Wales Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059824794","display_name":"XIANZHI WANG","orcid":null},"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":"Xianzhi Wang","raw_affiliation_strings":["University of Technology Sydney  Sydney New South Wales Australia"],"raw_orcid":"https://orcid.org/0000-0001-9582-3445","affiliations":[{"raw_affiliation_string":"University of Technology Sydney  Sydney New South Wales Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062128133"],"corresponding_institution_ids":["https://openalex.org/I114017466","https://openalex.org/I199693650"],"apc_list":{"value":3860,"currency":"USD","value_usd":3860},"apc_paid":{"value":3860,"currency":"USD","value_usd":3860},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78949038,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"43","issue":"5","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":0.9435999989509583,"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":0.9435999989509583,"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":0.03020000085234642,"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"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.0024999999441206455,"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/credit-card-fraud","display_name":"Credit card fraud","score":0.6880999803543091},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6771000027656555},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5777000188827515},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5771999955177307},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5631999969482422},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5195000171661377},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4805000126361847},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.4268999993801117}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8806999921798706},{"id":"https://openalex.org/C2780747020","wikidata":"https://www.wikidata.org/wiki/Q83873","display_name":"Credit card fraud","level":4,"score":0.6880999803543091},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6771000027656555},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6556000113487244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5989000201225281},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5777000188827515},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5771999955177307},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5631999969482422},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5195000171661377},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4805000126361847},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.4268999993801117},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.39969998598098755},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.39739999175071716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3727000057697296},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1111/exsy.70256","is_oa":true,"landing_page_url":"https://doi.org/10.1111/exsy.70256","pdf_url":null,"source":{"id":"https://openalex.org/S72232612","display_name":"Expert Systems","issn_l":"0266-4720","issn":["0266-4720","1468-0394"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1111/exsy.70256","is_oa":true,"landing_page_url":"https://doi.org/10.1111/exsy.70256","pdf_url":null,"source":{"id":"https://openalex.org/S72232612","display_name":"Expert Systems","issn_l":"0266-4720","issn":["0266-4720","1468-0394"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6371501684188843}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1985258161","https://openalex.org/W2112796928","https://openalex.org/W2119821739","https://openalex.org/W2217007515","https://openalex.org/W2295598076","https://openalex.org/W2743138268","https://openalex.org/W2779931100","https://openalex.org/W2786577118","https://openalex.org/W2902636447","https://openalex.org/W2911964244","https://openalex.org/W3048656210","https://openalex.org/W3134261669","https://openalex.org/W3142722547","https://openalex.org/W3149839747","https://openalex.org/W3160246678","https://openalex.org/W3199368817","https://openalex.org/W3201015557","https://openalex.org/W4210242534","https://openalex.org/W4307644119","https://openalex.org/W4309048484","https://openalex.org/W4317233797","https://openalex.org/W4321021182","https://openalex.org/W4324046881","https://openalex.org/W4360995349","https://openalex.org/W4375947334","https://openalex.org/W4377101177","https://openalex.org/W4380537293","https://openalex.org/W4380997613","https://openalex.org/W4385627258","https://openalex.org/W4385976039","https://openalex.org/W4386630125","https://openalex.org/W4387092382","https://openalex.org/W4387500911","https://openalex.org/W4389076770","https://openalex.org/W4389538119","https://openalex.org/W4390547231","https://openalex.org/W4391688210","https://openalex.org/W4392173133","https://openalex.org/W4392502993","https://openalex.org/W4396521123","https://openalex.org/W4396620566","https://openalex.org/W4400131777","https://openalex.org/W4400770653","https://openalex.org/W4403071743","https://openalex.org/W4403547784","https://openalex.org/W4403826670","https://openalex.org/W4403891789","https://openalex.org/W4404024016","https://openalex.org/W4404351449","https://openalex.org/W4405488429","https://openalex.org/W4406082863","https://openalex.org/W4407081435","https://openalex.org/W4408524291","https://openalex.org/W4409556603","https://openalex.org/W4411832138","https://openalex.org/W4412648774","https://openalex.org/W4413935224","https://openalex.org/W4414925088","https://openalex.org/W4415008673","https://openalex.org/W4415206736","https://openalex.org/W7082451233","https://openalex.org/W7133217623"],"related_works":[],"abstract_inverted_index":{"ABSTRACT":[0],"Credit":[1],"card":[2],"fraud":[3,118,165,216],"detection":[4,166,228],"remains":[5],"a":[6,80,108,127,133,148,179,238],"challenging":[7],"research":[8],"problem":[9],"due":[10],"to":[11,47,101,114],"the":[12,18,40,121,153,170,198,205,208,222],"class":[13],"imbalance":[14],"issue":[15],"caused":[16],"by":[17,193],"rarity":[19],"of":[20,43,135,158,182,187,207],"fraudulent":[21],"transactions.":[22],"Classical":[23],"oversampling":[24],"techniques":[25],"such":[26],"as":[27,71],"SMOTE,":[28],"ADASYN":[29],"and":[30,59,69,90,104,130,147,162,184,214,240],"their":[31],"variants":[32],"help":[33],"balance":[34],"data":[35],"but":[36,64,233],"do":[37],"not":[38,225],"reflect":[39],"nonlinear":[41],"structure":[42],"real\u2010world":[44],"fraud,":[45],"leading":[46],"poor":[48],"generalization.":[49],"Recent":[50],"state\u2010of\u2010the\u2010art":[51,163],"hybrid":[52,164],"frameworks":[53],"that":[54,84,175,221],"combine":[55],"deep":[56],"generative":[57,88],"models":[58],"ensemble":[60,92,146],"learning":[61],"improve":[62],"performance":[63],"treat":[65],"representation":[66,86],"learning,":[67,87],"augmentation":[68,89],"fusion":[70,128],"disconnected":[72],"stages.":[73],"To":[74],"address":[75],"these":[76,112],"limitations,":[77],"we":[78],"propose":[79],"unified":[81],"multistage":[82],"framework":[83,95,154,210,224],"integrates":[85],"intelligent":[91,145],"fusion.":[93],"Our":[94],"first":[96],"extracts":[97],"autoencoder\u2010based":[98],"latent":[99],"representations":[100],"capture":[102],"discriminative":[103],"interpretable":[105],"features;":[106],"then,":[107],"label\u2010conditioned":[109],"VAE\u2010GAN":[110],"uses":[111],"embeddings":[113],"generate":[115],"realistic":[116],"synthetic":[117],"samples;":[119],"finally,":[120],"enriched":[122],"features":[123],"are":[124,140],"projected":[125],"into":[126],"space":[129],"classified":[131],"using":[132],"pool":[134],"diverse":[136],"learners,":[137],"whose":[138],"outputs":[139],"consolidated":[141],"through":[142],"an":[143],"embedding\u2010aware":[144],"meta\u2010ensemble":[149],"layer.":[150],"We":[151],"benchmark":[152],"against":[155],"two":[156],"categories":[157,192],"baselines:":[159],"oversampling\u2010based":[160],"methods":[161],"systems.":[167],"Experiments":[168],"on":[169,197,211],"European":[171],"cardholder":[172],"dataset":[173,202],"show":[174],"our":[176],"approach":[177],"achieves":[178],"macro":[180],"F1\u2010score":[181],"95.15%":[183],"balanced":[185],"accuracy":[186,229],"92.85%,":[188],"outperforming":[189],"both":[190],"baseline":[191],"2.8%.":[194],"Additional":[195],"experiments":[196],"IEEE\u2010CIS":[199],"Fraud":[200],"Detection":[201],"further":[203],"validate":[204],"generalizability":[206],"proposed":[209,223],"large\u2010scale,":[212],"heterogeneous":[213],"feature\u2010rich":[215],"data.":[217],"The":[218],"results":[219],"demonstrate":[220],"only":[226],"improves":[227],"under":[230],"severe":[231],"imbalances":[232],"also":[234],"maintains":[235],"interpretability,":[236],"offering":[237],"robust":[239],"scalable":[241],"foundation":[242],"for":[243],"reliable":[244],"financial":[245],"risk":[246],"control.":[247]},"counts_by_year":[],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2026-04-10T00:00:00"}
