{"id":"https://openalex.org/W2586620891","doi":"https://doi.org/10.1108/k-06-2016-0158","title":"Simplifying credit scoring rules using LVQ + PSO","display_name":"Simplifying credit scoring rules using LVQ + PSO","publication_year":2017,"publication_date":"2017-01-09","ids":{"openalex":"https://openalex.org/W2586620891","doi":"https://doi.org/10.1108/k-06-2016-0158","mag":"2586620891"},"language":"en","primary_location":{"id":"doi:10.1108/k-06-2016-0158","is_oa":false,"landing_page_url":"https://doi.org/10.1108/k-06-2016-0158","pdf_url":null,"source":{"id":"https://openalex.org/S168682784","display_name":"Kybernetes","issn_l":"0368-492X","issn":["0368-492X","1758-7883"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kybernetes","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1704.04450","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Laura Cristina Lanzarini","orcid":null},"institutions":[{"id":"https://openalex.org/I874386039","display_name":"Universidad Nacional de La Plata","ror":"https://ror.org/01tjs6929","country_code":"AR","type":"education","lineage":["https://openalex.org/I874386039"]}],"countries":["AR"],"is_corresponding":true,"raw_author_name":"Laura Cristina Lanzarini","raw_affiliation_strings":["Universidad Nacional de la Plata, Facultad de Inform\u00e1tica, III-LIDI, La Plata, Argentina"],"affiliations":[{"raw_affiliation_string":"Universidad Nacional de la Plata, Facultad de Inform\u00e1tica, III-LIDI, La Plata, Argentina","institution_ids":["https://openalex.org/I874386039"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Augusto Villa Monte","orcid":null},"institutions":[{"id":"https://openalex.org/I874386039","display_name":"Universidad Nacional de La Plata","ror":"https://ror.org/01tjs6929","country_code":"AR","type":"education","lineage":["https://openalex.org/I874386039"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Augusto Villa Monte","raw_affiliation_strings":["Universidad Nacional de la Plata, Facultad de Inform\u00e1tica, III-LIDI, La Plata, Argentina"],"affiliations":[{"raw_affiliation_string":"Universidad Nacional de la Plata, Facultad de Inform\u00e1tica, III-LIDI, La Plata, Argentina","institution_ids":["https://openalex.org/I874386039"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Aurelio F. Bariviera","orcid":null},"institutions":[{"id":"https://openalex.org/I55952717","display_name":"Universidad Rovira i Virgili","ror":"https://ror.org/00g5sqv46","country_code":"ES","type":"education","lineage":["https://openalex.org/I55952717"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Aurelio F. Bariviera","raw_affiliation_strings":["Department of Business, Universitat Rovira i Virgili, Reus, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Business, Universitat Rovira i Virgili, Reus, Spain","institution_ids":["https://openalex.org/I55952717"]}]},{"author_position":"last","author":{"id":null,"display_name":"Patricia Jimbo Santana","orcid":null},"institutions":[{"id":"https://openalex.org/I141930428","display_name":"Central University of Ecuador","ror":"https://ror.org/010n0x685","country_code":"EC","type":"education","lineage":["https://openalex.org/I141930428"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Patricia Jimbo Santana","raw_affiliation_strings":["Facultad de Ciencias Administrativas, Universidad Central del Ecuador, Quito, Pichincha, Ecuador"],"affiliations":[{"raw_affiliation_string":"Facultad de Ciencias Administrativas, Universidad Central del Ecuador, Quito, Pichincha, Ecuador","institution_ids":["https://openalex.org/I141930428"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I874386039"],"apc_list":null,"apc_paid":null,"fwci":9.3886,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.97520645,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"46","issue":"1","first_page":"8","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.993399977684021,"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":0.993399977684021,"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":0.0008999999845400453,"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":0.000699999975040555,"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/learning-vector-quantization","display_name":"Learning vector quantization","score":0.8974999785423279},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6840999722480774},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.557200014591217},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5177000164985657},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5055000185966492},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.42500001192092896},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4242999851703644},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.38960000872612}],"concepts":[{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.8974999785423279},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6840999722480774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6385999917984009},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.557200014591217},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5177000164985657},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5055000185966492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49320000410079956},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4765999913215637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4422000050544739},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.42500001192092896},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4242999851703644},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C77783676","wikidata":"https://www.wikidata.org/wiki/Q15218588","display_name":"Credit analysis","level":4,"score":0.29679998755455017},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1108/k-06-2016-0158","is_oa":false,"landing_page_url":"https://doi.org/10.1108/k-06-2016-0158","pdf_url":null,"source":{"id":"https://openalex.org/S168682784","display_name":"Kybernetes","issn_l":"0368-492X","issn":["0368-492X","1758-7883"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kybernetes","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1704.04450","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1704.04450","pdf_url":"https://arxiv.org/pdf/1704.04450","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1704.04450","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1704.04450","pdf_url":"https://arxiv.org/pdf/1704.04450","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W976137010","https://openalex.org/W1506285740","https://openalex.org/W1527282796","https://openalex.org/W1528113134","https://openalex.org/W1587610203","https://openalex.org/W1596270182","https://openalex.org/W1990517717","https://openalex.org/W2014958596","https://openalex.org/W2124532504","https://openalex.org/W2125213524","https://openalex.org/W2131816657","https://openalex.org/W2152195021","https://openalex.org/W2168123127","https://openalex.org/W2208635417","https://openalex.org/W2399828986","https://openalex.org/W4211007335"],"related_works":[],"abstract_inverted_index":{"Purpose":[0],"One":[1,400],"of":[2,15,37,57,61,91,108,112,119,122,145,180,189,197,213,219,296,317,330,378,402,470],"the":[3,7,12,44,58,106,120,181,194,198,207,226,230,235,294,335,360,363,369],"key":[4,89],"elements":[5],"in":[6,229,243,259,264,271,281,349,436,474],"banking":[8,247],"industry":[9],"relies":[10],"on":[11,80,85,289],"appropriate":[13],"selection":[14],"customers.":[16,345],"To":[17],"manage":[18],"credit":[19,139,152,260,312,357,419,424,437],"risk,":[20],"banks":[21],"dedicate":[22],"special":[23],"efforts":[24],"to":[25,29,73,155,205,223,307,323,340,343,353,367,374,408,412,414,443,466],"classify":[26],"customers":[27,309],"according":[28],"their":[30],"risk.":[31],"The":[32,88,142,315],"usual":[33],"decision-making":[34],"process":[35],"consists":[36],"gathering":[38],"personal":[39],"and":[40,52,98,193,216,384,397,459],"financial":[41,303,320,364,398,472],"information":[42,48],"about":[43,158,173],"borrower.":[45],"Processing":[46],"this":[47,92,148],"can":[49],"be":[50],"time-consuming,":[51],"presents":[53,66],"some":[54],"difficulties":[55],"because":[56,118],"heterogeneous":[59],"structure":[60],"data.":[62],"Design/methodology/approach":[63],"This":[64,115,326,447],"paper":[65],"an":[67,128,167,210,241,269,460],"alternative":[68],"method":[69,149,452],"that":[70,76,183,284,453],"is":[71,105,116,202,248,278,305,348,407],"able":[72],"generate":[74,427],"rules":[75,133,146,411,426],"work":[77],"not":[78],"only":[79,253],"numerical":[81],"attributes":[82],"but":[83,267],"also":[84,163,268],"nominal":[86],"ones.":[87],"feature":[90],"method,":[93],"called":[94],"learning":[95],"vector":[96],"quantization":[97],"particle":[99],"swarm":[100],"optimization":[101,129,461],"(LVQ":[102],"+":[103],"PSO),":[104],"finding":[107],"a":[109,123,135,160,217,249,257,297,302,319,355,375,382,389,405,418,450,455,467,471,475],"reduced":[110,143],"set":[111],"classifying":[113],"rules.":[114],"possible":[117],"combination":[121],"competitive":[124,456],"neural":[125,457],"network":[126,212,458],"with":[127,301,310],"technique.":[130,462],"Findings":[131],"These":[132],"constitute":[134],"predictive":[136],"model":[137],"for":[138,151,169],"risk":[140,429],"approval.":[141],"quantity":[144],"makes":[147],"useful":[150],"officers":[153],"aiming":[154],"make":[156],"decisions":[157],"granting":[159],"credit.":[161,245],"It":[162,463],"could":[164],"act":[165],"as":[166],"orientation":[168],"borrower\u2019s":[170],"self":[171],"evaluation":[172],"her/his":[174],"creditworthiness.":[175],"Research":[176],"limitations/implications":[177],"In":[178,234,291,431],"spite":[179],"fact":[182],"conducted":[184],"tests":[185],"showed":[186],"no":[187],"evidence":[188],"dependence":[190],"between":[191,393],"results":[192],"initial":[195],"size":[196,215],"LVQ":[199,211],"network,":[200],"it":[201,277,347,433],"considered":[203],"desirable":[204],"repeat":[206],"measurements":[208],"using":[209],"minimum":[214],"version":[218],"variable":[220],"population":[221],"PSO":[222],"adequately":[224],"explore":[225],"solution":[227],"space":[228],"future.":[231],"Practical":[232],"implications":[233,422],"past":[236],"decades,":[237],"there":[238,255],"has":[239,254],"been":[240,256],"increase":[242,270],"consumer":[244],"Retail":[246],"growing":[250],"industry.":[251],"Not":[252],"boom":[258],"card":[261],"memberships,":[262],"specially":[263],"emerging":[265,282],"economies,":[266],"small":[272],"consumption":[273],"credits.":[274],"For":[275],"example,":[276],"very":[279],"common":[280],"economies":[283],"families":[285],"buy":[286],"home":[287,298,336,394],"appliances":[288,395],"installments.":[290],"those":[292],"countries,":[293],"association":[295,327],"appliance":[299,337],"shop":[300,338],"institution":[304,365,473],"usual,":[306],"provide":[308],"quick-decision":[311],"line":[313],"facilities.":[314],"existence":[316],"such":[318,404],"instrument":[321],"aids":[322],"boost":[324],"sales.":[325],"generates":[328],"conflict":[329],"interests.":[331],"On":[332,359],"one":[333],"hand,":[334,362],"wants":[339,366],"sell":[341],"products":[342],"all":[344],"Therefore,":[346],"its":[350],"best":[351],"interest":[352],"promote":[354],"generous":[356],"policy.":[358],"other":[361],"maximize":[368],"revenue":[370],"from":[371],"credits,":[372],"leading":[373],"strict":[376],"surveillance":[377],"loan":[379],"losses.":[380],"Having":[381],"fair":[383],"transparent":[385],"credit-granting":[386],"policy":[387,406],"favors":[388],"good":[390],"business":[391],"relationship":[392],"shops":[396],"institutions.":[399],"way":[401],"developing":[403,476],"construct":[409],"objective":[410],"decide":[413],"grant":[415],"or":[416],"deny":[417],"application.":[420],"Social":[421],"Better":[423],"decision":[425],"enhanced":[428],"sharing.":[430],"addition,":[432],"improves":[434],"transparency":[435],"acceptance":[438],"decisions,":[439],"giving":[440],"less":[441],"room":[442],"arbitrary":[444],"decisions.":[445],"Originality/value":[446],"study":[448],"develops":[449],"new":[451],"combines":[454],"was":[464],"applied":[465],"real":[468],"database":[469],"country.":[477]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2017-02-17T00:00:00"}