{"id":"https://openalex.org/W4412634278","doi":"https://doi.org/10.1007/s42979-025-04222-8","title":"Lending by Algorithm: Fair or Flawed? An Information-Theoretic View of Credit Decision Pipelines","display_name":"Lending by Algorithm: Fair or Flawed? An Information-Theoretic View of Credit Decision Pipelines","publication_year":2025,"publication_date":"2025-07-24","ids":{"openalex":"https://openalex.org/W4412634278","doi":"https://doi.org/10.1007/s42979-025-04222-8"},"language":"en","primary_location":{"id":"doi:10.1007/s42979-025-04222-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-04222-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-04222-8.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-04222-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017885914","display_name":"Sayyed Khawar Abbas","orcid":"https://orcid.org/0000-0001-7179-1899"},"institutions":[{"id":"https://openalex.org/I163245316","display_name":"Corvinus University of Budapest","ror":"https://ror.org/01vxfm326","country_code":"HU","type":"education","lineage":["https://openalex.org/I163245316"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"Sayyed Khawar Abbas","raw_affiliation_strings":["Department of Information Systems, Institute of Data Analytics and Information Systems, Corvinus University of Budapest, 8 Fovam Ter, 1093, Budapest, Hungary"],"raw_orcid":"https://orcid.org/0000-0001-7179-1899","affiliations":[{"raw_affiliation_string":"Department of Information Systems, Institute of Data Analytics and Information Systems, Corvinus University of Budapest, 8 Fovam Ter, 1093, Budapest, Hungary","institution_ids":["https://openalex.org/I163245316"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5017885914"],"corresponding_institution_ids":["https://openalex.org/I163245316"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":8.1189,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.97525679,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"6","issue":"6","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10127","display_name":"Banking stability, regulation, efficiency","score":0.9919000267982483,"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"}},"topics":[{"id":"https://openalex.org/T10127","display_name":"Banking stability, regulation, efficiency","score":0.9919000267982483,"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"}},{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.9804999828338623,"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"}},{"id":"https://openalex.org/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9764000177383423,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.459457665681839},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.43680012226104736},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3734028935432434},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.3369787335395813},{"id":"https://openalex.org/keywords/actuarial-science","display_name":"Actuarial science","score":0.32019469141960144},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15743717551231384}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.459457665681839},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.43680012226104736},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3734028935432434},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3369787335395813},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.32019469141960144},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15743717551231384},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s42979-025-04222-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-04222-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-04222-8.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:unipub.lib.uni-corvinus.hu:11608","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s42979-025-04222-8>","pdf_url":null,"source":{"id":"https://openalex.org/S4306400280","display_name":"Corvinus Research Archive (Corvinus University of Budapest)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I163245316","host_organization_name":"Corvinus University of Budapest","host_organization_lineage":["https://openalex.org/I163245316"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":{"id":"doi:10.1007/s42979-025-04222-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-04222-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-04222-8.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320318030","display_name":"Budapesti Corvinus Egyetem","ror":"https://ror.org/01vxfm326"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412634278.pdf","grobid_xml":"https://content.openalex.org/works/W4412634278.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W3125704451","https://openalex.org/W3137762516","https://openalex.org/W3153888608","https://openalex.org/W3165610121","https://openalex.org/W3186071540","https://openalex.org/W3197802183","https://openalex.org/W3212180848","https://openalex.org/W4306874567","https://openalex.org/W4312218229","https://openalex.org/W4321105716","https://openalex.org/W4367182589","https://openalex.org/W4376958471","https://openalex.org/W4380486661","https://openalex.org/W4386885190","https://openalex.org/W4387187944","https://openalex.org/W4389735984","https://openalex.org/W4390765683","https://openalex.org/W4392515337","https://openalex.org/W4394811799","https://openalex.org/W4394903832","https://openalex.org/W4394904089","https://openalex.org/W4396797028","https://openalex.org/W4396930885","https://openalex.org/W4399663041","https://openalex.org/W4399699153","https://openalex.org/W4400308575","https://openalex.org/W4400414268","https://openalex.org/W4402194361","https://openalex.org/W4402824598","https://openalex.org/W4402878960","https://openalex.org/W4403963503","https://openalex.org/W4406097795","https://openalex.org/W4409473861","https://openalex.org/W4410890108","https://openalex.org/W4410959209","https://openalex.org/W6963161203"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Abstract":[0],"As":[1],"artificial":[2],"intelligence":[3],"(AI)":[4],"becomes":[5],"increasingly":[6],"embedded":[7],"in":[8,22,157,262],"financial":[9,155],"decision-making,":[10],"questions":[11],"of":[12,33,70,78,187,246],"fairness,":[13],"transparency,":[14],"and":[15,39,60,80,127,154,161,182,200,215,252,292,301],"trust":[16],"have":[17],"taken":[18],"center":[19],"stage,":[20],"particularly":[21],"high-stakes":[23],"domains":[24],"like":[25],"credit":[26,35,250],"allocation.":[27],"This":[28],"study":[29],"investigates":[30],"the":[31,120,158,166,174,212,226,244,259,266,282],"use":[32],"AI-based":[34],"scoring":[36,131],"for":[37,243,254],"small":[38],"medium-sized":[40],"enterprises":[41],"(SMEs),":[42],"combining":[43],"algorithmic":[44,130],"performance":[45,271],"analysis":[46,205],"with":[47,96,108,151],"behavioral":[48,194,247],"insights":[49],"from":[50],"affected":[51],"users.":[52],"Using":[53],"a":[54,62,67,101,207],"convergent":[55],"mixed-methods":[56],"design,":[57],"we":[58,146],"train":[59],"evaluate":[61],"random":[63],"forest":[64],"classifier":[65],"on":[66,193,228],"US":[68],"dataset":[69,285],"5000":[71],"anonymized":[72,284],"loan":[73],"applications,":[74],"achieving":[75],"an":[76,124],"AUC":[77],"0.998":[79],"simulating":[81],"real-world":[82],"lending":[83,305],"conditions.":[84],"Fairness":[85],"diagnostics":[86],"reveal":[87],"that":[88,233,257],"approval":[89],"rates":[90,115],"differ":[91],"significantly":[92],"by":[93,231],"education":[94],"level,":[95],"low-education":[97],"applicants":[98],"approved":[99],"at":[100],"rate":[102],"three":[103],"times":[104],"lower":[105],"than":[106],"those":[107],"advanced":[109,308],"degrees,":[110],"despite":[111],"similar":[112],"false":[113],"positive":[114],"across":[116],"groups.":[117],"We":[118,241],"frame":[119],"decision":[121],"pipeline":[122],"as":[123,180,197,219,290],"information-processing":[125],"system":[126],"consider":[128],"how":[129],"may":[132],"distort":[133],"or":[134,221],"reduce":[135],"informational":[136],"signals":[137],"relevant":[138],"to":[139],"perceived":[140],"fairness.":[141,240],"To":[142],"contextualize":[143],"these":[144],"findings,":[145],"conduct":[147],"twelve":[148],"semi-structured":[149],"interviews":[150],"SME":[152],"owners":[153],"managers":[156],"United":[159,162],"States":[160],"Kingdom,":[163],"coded":[164],"using":[165],"Capability,":[167],"Opportunity,":[168],"Motivation,":[169],"Behavior":[170],"(COM-B)":[171],"framework.":[172],"While":[173,265],"model":[175,267],"privileges":[176],"structural":[177],"features":[178],"such":[179,196,289],"income":[181],"digital":[183],"banking":[184],"activity,":[185],"indicators":[186,248],"\u201ccapability\u201d,":[188],"participants":[189],"place":[190],"greater":[191],"emphasis":[192],"cues":[195],"payment":[198],"reliability":[199],"business":[201],"resilience.":[202],"A":[203],"triangulated":[204],"reveals":[206],"stark":[208],"misalignment":[209],"between":[210],"what":[211,216],"algorithm":[213],"recognizes":[214],"users":[217],"perceive":[218],"fair":[220],"valid.":[222],"Our":[223],"findings":[224,302],"advance":[225],"discourse":[227],"AI":[229],"ethics":[230],"demonstrating":[232],"statistical":[234],"fairness":[235,296],"does":[236],"not":[237,298],"guarantee":[238],"experiential":[239],"advocate":[242],"integration":[245],"into":[249],"models":[251],"call":[253],"policy":[255],"reforms":[256],"address":[258],"socio-technical":[260],"gaps":[261],"automated":[263],"finance.":[264],"demonstrates":[268],"high":[269],"predictive":[270],"(AUC":[272],"~":[273],"0.998),":[274],"this":[275],"result":[276],"should":[277],"be":[278,299],"interpreted":[279],"cautiously":[280],"given":[281],"constrained,":[283],"lacking":[286],"demographic":[287],"attributes":[288],"gender":[291],"race.":[293],"Consequently,":[294],"intersectional":[295],"could":[297],"evaluated,":[300],"primarily":[303],"reflect":[304],"contexts":[306],"within":[307],"economies.":[309]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
