{"id":"https://openalex.org/W7154252042","doi":"https://doi.org/10.1140/epjds/s13688-026-00655-0","title":"A row-type specific hybrid framework for credit risk analysis: loan portfolio based feature selection and unsupervised Bayesian network dependency exploration","display_name":"A row-type specific hybrid framework for credit risk analysis: loan portfolio based feature selection and unsupervised Bayesian network dependency exploration","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154252042","doi":"https://doi.org/10.1140/epjds/s13688-026-00655-0"},"language":"en","primary_location":{"id":"doi:10.1140/epjds/s13688-026-00655-0","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-026-00655-0","pdf_url":null,"source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"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":"EPJ Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1140/epjds/s13688-026-00655-0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111078871","display_name":"Minati Rath","orcid":null},"institutions":[{"id":"https://openalex.org/I44430492","display_name":"Indian Institute of Management Bangalore","ror":"https://ror.org/02xxpjq61","country_code":"IN","type":"education","lineage":["https://openalex.org/I44430492"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Minati Rath","raw_affiliation_strings":["Department of Analytics and Decision Science, Indian Institute of Management (IIM), Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Analytics and Decision Science, Indian Institute of Management (IIM), Mumbai, India","institution_ids":["https://openalex.org/I44430492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104200664","display_name":"Hema Date","orcid":null},"institutions":[{"id":"https://openalex.org/I44430492","display_name":"Indian Institute of Management Bangalore","ror":"https://ror.org/02xxpjq61","country_code":"IN","type":"education","lineage":["https://openalex.org/I44430492"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hema Date","raw_affiliation_strings":["Department of Analytics and Decision Science, Indian Institute of Management (IIM), Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Analytics and Decision Science, Indian Institute of Management (IIM), Mumbai, India","institution_ids":["https://openalex.org/I44430492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5111078871"],"corresponding_institution_ids":["https://openalex.org/I44430492"],"apc_list":{"value":1690,"currency":"USD","value_usd":1690},"apc_paid":{"value":1690,"currency":"USD","value_usd":1690},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3740074,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","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":0.9855999946594238,"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":0.9855999946594238,"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/T11496","display_name":"Credit Risk and Financial Regulations","score":0.0027000000700354576,"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/T10987","display_name":"Microfinance and Financial Inclusion","score":0.0012000000569969416,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"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/credit-risk","display_name":"Credit risk","score":0.7099999785423279},{"id":"https://openalex.org/keywords/loan","display_name":"Loan","score":0.654699981212616},{"id":"https://openalex.org/keywords/collateral","display_name":"Collateral","score":0.6172999739646912},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5893999934196472},{"id":"https://openalex.org/keywords/probability-of-default","display_name":"Probability of default","score":0.4959999918937683},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.46540001034736633},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.460999995470047},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.44940000772476196},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.42969998717308044}],"concepts":[{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.7099999785423279},{"id":"https://openalex.org/C2777764128","wikidata":"https://www.wikidata.org/wiki/Q189539","display_name":"Loan","level":2,"score":0.654699981212616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6201000213623047},{"id":"https://openalex.org/C2777910564","wikidata":"https://www.wikidata.org/wiki/Q694563","display_name":"Collateral","level":2,"score":0.6172999739646912},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5893999934196472},{"id":"https://openalex.org/C2779806880","wikidata":"https://www.wikidata.org/wiki/Q778470","display_name":"Probability of default","level":3,"score":0.4959999918937683},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4871000051498413},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.46540001034736633},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.460999995470047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4562999904155731},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.44940000772476196},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.42969998717308044},{"id":"https://openalex.org/C2780821815","wikidata":"https://www.wikidata.org/wiki/Q5340806","display_name":"Portfolio","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.375900000333786},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3571999967098236},{"id":"https://openalex.org/C2983355114","wikidata":"https://www.wikidata.org/wiki/Q161380","display_name":"Credit card","level":3,"score":0.35120001435279846},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C139043278","wikidata":"https://www.wikidata.org/wiki/Q837171","display_name":"Financial services","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.2976999878883362},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.29760000109672546},{"id":"https://openalex.org/C32896092","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Risk management","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C2780759654","wikidata":"https://www.wikidata.org/wiki/Q809934","display_name":"Basel II","level":4,"score":0.28209999203681946},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.27869999408721924},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C51034333","wikidata":"https://www.wikidata.org/wiki/Q4747796","display_name":"Amortizing loan","level":5,"score":0.2500999867916107}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1140/epjds/s13688-026-00655-0","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-026-00655-0","pdf_url":null,"source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"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":"EPJ Data Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8449363f46374b3083cc50b42ccbb0ef","is_oa":true,"landing_page_url":"https://doaj.org/article/8449363f46374b3083cc50b42ccbb0ef","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":"EPJ Data Science, Vol 15, Iss 1 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1140/epjds/s13688-026-00655-0","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-026-00655-0","pdf_url":null,"source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"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":"EPJ Data Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1128184534","https://openalex.org/W1819762691","https://openalex.org/W1977009091","https://openalex.org/W1979638902","https://openalex.org/W1982120517","https://openalex.org/W2064031858","https://openalex.org/W2131816657","https://openalex.org/W2148143831","https://openalex.org/W2282821441","https://openalex.org/W2794772509","https://openalex.org/W2945976633","https://openalex.org/W3000463950","https://openalex.org/W3014951338","https://openalex.org/W3026030307","https://openalex.org/W3045991306","https://openalex.org/W3086653191","https://openalex.org/W3121879727","https://openalex.org/W3134447554","https://openalex.org/W3176827378","https://openalex.org/W3183251913","https://openalex.org/W4223538073","https://openalex.org/W4233116977","https://openalex.org/W4281743691","https://openalex.org/W4293386229","https://openalex.org/W4323267933","https://openalex.org/W4381997116","https://openalex.org/W4387226873","https://openalex.org/W4392187129","https://openalex.org/W4411384686"],"related_works":[],"abstract_inverted_index":{"Credit":[0,61],"risk":[1,77,93,118,228,279],"assessment":[2],"is":[3,130,232],"a":[4,26,69],"critical":[5],"function":[6],"in":[7,35,170,192,229],"financial":[8,46,137],"analytics,":[9],"requiring":[10],"models":[11],"that":[12,169,226,249],"can":[13],"adapt":[14],"to":[15,40,95,132,236],"diverse":[16],"borrower":[17,227,282],"profiles":[18],"while":[19],"providing":[20],"clear":[21],"and":[22,55,88,157,181,196,215,222,239,260,265],"interpretable":[23,252],"insights.":[24],"Although":[25],"range":[27],"of":[28,45,92,124,277],"data":[29,47,84,247,274],"driven":[30,275],"techniques":[31],"have":[32],"been":[33],"applied":[34,131],"this":[36,121,230],"domain,":[37],"many":[38],"struggle":[39],"handle":[41],"the":[42,83,90,102,204,278],"inherent":[43],"heterogeneity":[44],"across":[48],"different":[49],"loan":[50,86],"categories":[51,94],"such":[52,175,218],"as":[53,176,185,219],"personal":[54,171],"agricultural":[56,202],"loans.":[57],"This":[58,145],"paper":[59],"introduces":[60],"Risk":[62],"Analysis":[63],"with":[64,116,151],"Bayesian":[65,127],"Networks":[66],"(CRAB-Net)":[67],",":[68],"row":[70],"type":[71,87],"specific":[72],"hybrid":[73],"framework":[74,167],"for":[75,201,263],"credit":[76,117],"modeling.":[78],"The":[79,166],"approach":[80],"first":[81],"segments":[82],"by":[85,210,271],"balances":[89],"distribution":[91],"ensure":[96],"fair":[97,256],"representation.":[98],"It":[99],"then":[100],"identifies":[101],"most":[103,114],"outcome":[104,143],"relevant":[105],"attributes":[106,217],"through":[107],"targeted":[108],"feature":[109],"selection,":[110],"focusing":[111],"on":[112,141,243],"variables":[113,138,174],"associated":[115],"differentiation.":[119],"On":[120],"refined":[122],"set":[123],"features,":[125],"unsupervised":[126,152],"network":[128,205],"learning":[129],"uncover":[133],"conditional":[134],"dependencies":[135],"among":[136],"without":[139],"relying":[140],"default":[142],"labels.":[144],"design":[146],"combines":[147],"supervised":[148],"relevance":[149],"filtering":[150],"dependency":[153,253],"discovery,":[154],"reducing":[155],"noise":[156],"avoiding":[158],"misleading":[159],"patterns":[160],"from":[161],"analyzing":[162],"all":[163],"features":[164],"indiscriminately.":[165],"revealed":[168],"loans,":[172,203],"installment-related":[173],"installment":[177],"frequency,":[178],"overdue":[179],"status,":[180],"repayment":[182,194],"structure":[183,206],"emerged":[184],"central":[186],"nodes,":[187],"indicating":[188],"their":[189],"dominant":[190],"role":[191],"defining":[193],"behavior":[195],"delinquency":[197],"risk.":[198],"In":[199],"contrast,":[200],"was":[207],"shaped":[208],"primarily":[209],"provisioning":[211],"norms,":[212],"landholding":[213],"details,":[214],"exposure-related":[216],"sanctioned":[220],"amount":[221],"collateral":[223,240],"type,":[224],"suggesting":[225],"segment":[231,257],"more":[233],"closely":[234],"linked":[235],"regulatory":[237],"classification":[238],"strength.":[241],"Experiments":[242],"real":[244],"world":[245],"banking":[246],"show":[248],"CRAB-Net":[250],"provides":[251],"graphs,":[254],"supports":[255],"level":[258],"analysis,":[259],"enhances":[261],"transparency":[262],"audit":[264],"supervisory":[266],"compliance":[267],"under":[268],"Basel":[269],"norms":[270],"offering":[272],"clear,":[273],"evidence":[276],"factors":[280],"shaping":[281],"outcomes.":[283]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2026-04-15T00:00:00"}