{"id":"https://openalex.org/W3165340137","doi":"https://doi.org/10.1186/s40537-021-00461-7","title":"Modelling customers credit card behaviour using bidirectional LSTM neural networks","display_name":"Modelling customers credit card behaviour using bidirectional LSTM neural networks","publication_year":2021,"publication_date":"2021-05-19","ids":{"openalex":"https://openalex.org/W3165340137","doi":"https://doi.org/10.1186/s40537-021-00461-7","mag":"3165340137"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-021-00461-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00461-7","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00461-7","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00461-7","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059618711","display_name":"Maher Alaraj","orcid":"https://orcid.org/0000-0001-9315-0670"},"institutions":[{"id":"https://openalex.org/I91044093","display_name":"Zayed University","ror":"https://ror.org/03snqfa66","country_code":"AE","type":"education","lineage":["https://openalex.org/I91044093"]}],"countries":["AE"],"is_corresponding":true,"raw_author_name":"Maher Ala\u2019raj","raw_affiliation_strings":["Department of Information Systems, College of Technological Innovation, Zayed University, 19282, Dubai, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0001-9315-0670","affiliations":[{"raw_affiliation_string":"Department of Information Systems, College of Technological Innovation, Zayed University, 19282, Dubai, United Arab Emirates","institution_ids":["https://openalex.org/I91044093"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091511508","display_name":"Maysam Abbod","orcid":"https://orcid.org/0000-0002-8515-7933"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maysam F. Abbod","raw_affiliation_strings":["Department of Electronic and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, Kingston Lane, Uxbridge, UB8 3PH, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, Kingston Lane, Uxbridge, UB8 3PH, UK","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064015558","display_name":"Munir Majdalawieh","orcid":"https://orcid.org/0000-0002-2559-7371"},"institutions":[{"id":"https://openalex.org/I91044093","display_name":"Zayed University","ror":"https://ror.org/03snqfa66","country_code":"AE","type":"education","lineage":["https://openalex.org/I91044093"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Munir Majdalawieh","raw_affiliation_strings":["Department of Information Systems, College of Technological Innovation, Zayed University, 19282, Dubai, United Arab Emirates"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems, College of Technological Innovation, Zayed University, 19282, Dubai, United Arab Emirates","institution_ids":["https://openalex.org/I91044093"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059618711"],"corresponding_institution_ids":["https://openalex.org/I91044093"],"apc_list":{"value":1990,"currency":"USD","value_usd":1990},"apc_paid":{"value":1990,"currency":"USD","value_usd":1990},"fwci":14.1432,"has_fulltext":true,"cited_by_count":76,"citation_normalized_percentile":{"value":0.99214556,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"8","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9998000264167786,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9947999715805054,"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/T11496","display_name":"Credit Risk and Financial Regulations","score":0.9520999789237976,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8187660574913025},{"id":"https://openalex.org/keywords/credit-card","display_name":"Credit card","score":0.7962111234664917},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6791762113571167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6660692691802979},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6031600832939148},{"id":"https://openalex.org/keywords/payment","display_name":"Payment","score":0.5840941667556763},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4991304874420166},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4905351996421814},{"id":"https://openalex.org/keywords/credit-score","display_name":"Credit score","score":0.4730096161365509},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4412645697593689},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.43244674801826477},{"id":"https://openalex.org/keywords/credit-card-fraud","display_name":"Credit card fraud","score":0.4180009663105011},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3341729938983917},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.32555365562438965},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.0953686535358429}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8187660574913025},{"id":"https://openalex.org/C2983355114","wikidata":"https://www.wikidata.org/wiki/Q161380","display_name":"Credit card","level":3,"score":0.7962111234664917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6791762113571167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6660692691802979},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6031600832939148},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.5840941667556763},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4991304874420166},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4905351996421814},{"id":"https://openalex.org/C2777138686","wikidata":"https://www.wikidata.org/wiki/Q1787103","display_name":"Credit score","level":2,"score":0.4730096161365509},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4412645697593689},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.43244674801826477},{"id":"https://openalex.org/C2780747020","wikidata":"https://www.wikidata.org/wiki/Q83873","display_name":"Credit card fraud","level":4,"score":0.4180009663105011},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3341729938983917},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.32555365562438965},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0953686535358429},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1186/s40537-021-00461-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00461-7","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00461-7","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:bura.brunel.ac.uk:2438/26499","is_oa":true,"landing_page_url":"https://bura.brunel.ac.uk/handle/2438/26499","pdf_url":"http://bura.brunel.ac.uk/bitstream/2438/26499/1/FullText.pdf","source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:8a3b28162504444e9c9671b527a4be49","is_oa":true,"landing_page_url":"https://doaj.org/article/8a3b28162504444e9c9671b527a4be49","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 8, Iss 1, Pp 1-27 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-021-00461-7","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00461-7","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00461-7","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4031860152","display_name":null,"funder_award_id":"R20053","funder_id":"https://openalex.org/F4320325295","funder_display_name":"Zayed University"}],"funders":[{"id":"https://openalex.org/F4320325295","display_name":"Zayed University","ror":"https://ror.org/03snqfa66"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3165340137.pdf","grobid_xml":"https://content.openalex.org/works/W3165340137.grobid-xml"},"referenced_works_count":81,"referenced_works":["https://openalex.org/W1479754761","https://openalex.org/W1493736340","https://openalex.org/W1531933838","https://openalex.org/W1565746575","https://openalex.org/W1569512666","https://openalex.org/W1586232474","https://openalex.org/W1605607952","https://openalex.org/W1697308463","https://openalex.org/W1971746503","https://openalex.org/W1980770954","https://openalex.org/W1982120517","https://openalex.org/W1985546543","https://openalex.org/W1990696070","https://openalex.org/W1992958333","https://openalex.org/W1994124263","https://openalex.org/W1994600722","https://openalex.org/W2003119650","https://openalex.org/W2015768982","https://openalex.org/W2029958983","https://openalex.org/W2052268454","https://openalex.org/W2052462336","https://openalex.org/W2053555865","https://openalex.org/W2061251466","https://openalex.org/W2064675550","https://openalex.org/W2065080511","https://openalex.org/W2073241381","https://openalex.org/W2085538972","https://openalex.org/W2085988980","https://openalex.org/W2088794999","https://openalex.org/W2098307847","https://openalex.org/W2103780778","https://openalex.org/W2119821739","https://openalex.org/W2130942839","https://openalex.org/W2131774270","https://openalex.org/W2131816657","https://openalex.org/W2133564696","https://openalex.org/W2135107350","https://openalex.org/W2137959503","https://openalex.org/W2143612262","https://openalex.org/W2146193817","https://openalex.org/W2163912736","https://openalex.org/W2165063012","https://openalex.org/W2167277498","https://openalex.org/W2168123127","https://openalex.org/W2169762136","https://openalex.org/W2185062546","https://openalex.org/W2336631262","https://openalex.org/W2409662531","https://openalex.org/W2475709057","https://openalex.org/W2582054354","https://openalex.org/W2665856277","https://openalex.org/W2739057980","https://openalex.org/W2768141904","https://openalex.org/W2782791108","https://openalex.org/W2786577118","https://openalex.org/W2787468747","https://openalex.org/W2788025656","https://openalex.org/W2789534793","https://openalex.org/W2799791930","https://openalex.org/W2809051652","https://openalex.org/W2895142658","https://openalex.org/W2897516981","https://openalex.org/W2902455138","https://openalex.org/W2904485001","https://openalex.org/W2911964244","https://openalex.org/W2948793373","https://openalex.org/W2962845528","https://openalex.org/W2970701626","https://openalex.org/W2978101659","https://openalex.org/W2999808656","https://openalex.org/W3048715644","https://openalex.org/W3095174976","https://openalex.org/W3095606640","https://openalex.org/W3124355498","https://openalex.org/W3124899688","https://openalex.org/W3138423578","https://openalex.org/W3141721705","https://openalex.org/W4239510810","https://openalex.org/W4297818331","https://openalex.org/W4388317054","https://openalex.org/W6679436768"],"related_works":["https://openalex.org/W2483711049","https://openalex.org/W4224237387","https://openalex.org/W3150316110","https://openalex.org/W4313247660","https://openalex.org/W3153799676","https://openalex.org/W2984276143","https://openalex.org/W4281702918","https://openalex.org/W4283392145","https://openalex.org/W3111672143","https://openalex.org/W4281858644"],"abstract_inverted_index":{"Abstract":[0],"With":[1],"the":[2,9,64,87,95,113,122,129,146,160,171,218,225],"rapid":[3],"growth":[4],"of":[5,12,67,97,124,170,183],"consumer":[6,88,219,232],"credit":[7,17,27,77,104,142,220,233],"and":[8,32,40,60,85,99,145,166,207],"huge":[10],"amount":[11],"financial":[13,41,46],"data":[14],"developing":[15],"effective":[16],"scoring":[18,28,76,221],"models":[19,29],"is":[20,70,110],"very":[21],"crucial.":[22],"Researchers":[23],"have":[24],"developed":[25],"complex":[26],"using":[30,80,152],"statistical":[31],"artificial":[33],"intelligence":[34],"(AI)":[35],"techniques":[36],"to":[37,43,71,92,120,192],"help":[38,72],"banks":[39],"institutions":[42],"support":[44,198],"their":[45],"decisions.":[47],"Neural":[48],"networks":[49],"are":[50,150],"considered":[51,180],"as":[52,156,181],"a":[53,125,140],"mostly":[54],"wide":[55],"used":[56],"technique":[57],"in":[58,75],"finance":[59],"business":[61],"applications.":[62],"Thus,":[63],"main":[65],"aim":[66],"this":[68],"paper":[69],"bank":[73],"management":[74],"card":[78,105,143],"clients":[79],"machine":[81,195],"learning":[82,196],"by":[83],"modelling":[84],"predicting":[86],"behaviour":[89],"with":[90,215],"respect":[91],"two":[93],"aspects:":[94],"probability":[96,123],"single":[98],"consecutive":[100],"missed":[101,126,184],"payments":[102,185],"for":[103,132],"customers.":[106],"The":[107,135,187],"proposed":[108],"model":[109,119,136,173,189],"based":[111,223],"on":[112,139,224],"bidirectional":[114],"Long-Short":[115],"Term":[116],"Memory":[117],"(LSTM)":[118],"give":[121],"payment":[127],"during":[128],"next":[130],"month":[131],"each":[133],"customer.":[134],"was":[137,190],"trained":[138],"real":[141],"dataset":[144],"customer":[147],"behavioural":[148],"scores":[149,174],"analysed":[151],"classical":[153],"measures":[154],"such":[155],"accuracy,":[157],"Area":[158],"Under":[159],"Curve,":[161],"Brier":[162],"score,":[163],"Kolmogorov\u2013Smirnov":[164],"test,":[165],"H-measure.":[167],"Calibration":[168],"analysis":[169],"LSTM":[172,188,226],"showed":[175],"that":[176],"they":[177],"can":[178],"be":[179],"probabilities":[182],".":[186],"compared":[191,214],"four":[193],"traditional":[194,216],"algorithms:":[197],"vector":[199],"machine,":[200],"random":[201],"forest,":[202],"multi-layer":[203],"perceptron":[204],"neural":[205,227],"network,":[206],"logistic":[208],"regression.":[209],"Experimental":[210],"results":[211],"show":[212],"that,":[213],"methods,":[217],"method":[222],"network":[228],"has":[229],"significantly":[230],"improved":[231],"scoring.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":5}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}
