{"id":"https://openalex.org/W4221099335","doi":"https://doi.org/10.1109/kst53302.2022.9729073","title":"Loan Default Risk Prediction Using Knowledge Graph","display_name":"Loan Default Risk Prediction Using Knowledge Graph","publication_year":2022,"publication_date":"2022-01-26","ids":{"openalex":"https://openalex.org/W4221099335","doi":"https://doi.org/10.1109/kst53302.2022.9729073"},"language":"en","primary_location":{"id":"doi:10.1109/kst53302.2022.9729073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst53302.2022.9729073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on Knowledge and Smart Technology (KST)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049044685","display_name":"Md. Nurul Alam","orcid":"https://orcid.org/0000-0003-0594-7781"},"institutions":[{"id":"https://openalex.org/I183697816","display_name":"Bangladesh University of Engineering and Technology","ror":"https://ror.org/05a1qpv97","country_code":"BD","type":"education","lineage":["https://openalex.org/I183697816"]}],"countries":["BD"],"is_corresponding":true,"raw_author_name":"Md. Nurul Alam","raw_affiliation_strings":["Bangladesh University of Engineering and Technology,Department of Computer Science and Engineering,Dhaka,Bangladesh"],"affiliations":[{"raw_affiliation_string":"Bangladesh University of Engineering and Technology,Department of Computer Science and Engineering,Dhaka,Bangladesh","institution_ids":["https://openalex.org/I183697816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075892647","display_name":"Muhammad Masroor Ali","orcid":"https://orcid.org/0000-0002-9336-043X"},"institutions":[{"id":"https://openalex.org/I183697816","display_name":"Bangladesh University of Engineering and Technology","ror":"https://ror.org/05a1qpv97","country_code":"BD","type":"education","lineage":["https://openalex.org/I183697816"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Muhammad Masroor Ali","raw_affiliation_strings":["Bangladesh University of Engineering and Technology,Department of Computer Science and Engineering,Dhaka,Bangladesh"],"affiliations":[{"raw_affiliation_string":"Bangladesh University of Engineering and Technology,Department of Computer Science and Engineering,Dhaka,Bangladesh","institution_ids":["https://openalex.org/I183697816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049044685"],"corresponding_institution_ids":["https://openalex.org/I183697816"],"apc_list":null,"apc_paid":null,"fwci":2.2424,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.88334305,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"34","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9945999979972839,"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":0.9945999979972839,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9129999876022339,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.803297221660614},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.758650541305542},{"id":"https://openalex.org/keywords/loan","display_name":"Loan","score":0.6981499791145325},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6242319941520691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5496944189071655},{"id":"https://openalex.org/keywords/credit-risk","display_name":"Credit risk","score":0.4754352569580078},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4451754689216614},{"id":"https://openalex.org/keywords/default","display_name":"Default","score":0.42850708961486816},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.29636403918266296},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.18043404817581177},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.09450948238372803}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.803297221660614},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758650541305542},{"id":"https://openalex.org/C2777764128","wikidata":"https://www.wikidata.org/wiki/Q189539","display_name":"Loan","level":2,"score":0.6981499791145325},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6242319941520691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5496944189071655},{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.4754352569580078},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4451754689216614},{"id":"https://openalex.org/C69637215","wikidata":"https://www.wikidata.org/wiki/Q702362","display_name":"Default","level":2,"score":0.42850708961486816},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.29636403918266296},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.18043404817581177},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.09450948238372803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/kst53302.2022.9729073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst53302.2022.9729073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 14th International Conference on Knowledge and Smart Technology (KST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W224398829","https://openalex.org/W1976846597","https://openalex.org/W2016366123","https://openalex.org/W2081180521","https://openalex.org/W2127795553","https://openalex.org/W2162397980","https://openalex.org/W2184957013","https://openalex.org/W2283196293","https://openalex.org/W2307376191","https://openalex.org/W2432356473","https://openalex.org/W2572147858","https://openalex.org/W2763321198","https://openalex.org/W2767287441","https://openalex.org/W2790611518","https://openalex.org/W2999309192","https://openalex.org/W3003265726","https://openalex.org/W3097734923","https://openalex.org/W3121456242","https://openalex.org/W4287643567","https://openalex.org/W6678830454","https://openalex.org/W6695596964","https://openalex.org/W6718112784","https://openalex.org/W6731801563","https://openalex.org/W6949974626"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4385561904","https://openalex.org/W3122155953","https://openalex.org/W3161551118","https://openalex.org/W606680577","https://openalex.org/W2612601761","https://openalex.org/W2768429096","https://openalex.org/W2808749691"],"abstract_inverted_index":{"Credit":[0],"risk,":[1,7],"also":[2],"known":[3],"as":[4,140],"loan":[5,47,114,154],"default":[6,48,115,155],"is":[8,77],"one":[9],"of":[10,25,54,80,146],"the":[11,23,26,51,68,72,125,144,147],"significant":[12],"financial":[13,18,36],"challenges":[14],"in":[15,45,71,152],"banking":[16],"and":[17,35,41,83,103,129],"institutions":[19,37],"since":[20],"it":[21],"involves":[22],"uncertainty":[24],"borrowers'":[27],"ability":[28],"to":[29,49,89,96,106,123],"perform":[30],"their":[31,64,101],"contractual":[32],"obligation.":[33],"Banks":[34],"rely":[38],"on":[39,119],"statistical":[40],"machine":[42,58,107,149],"learning":[43,59,108,150],"methods":[44],"predicting":[46,153],"reduce":[50],"potential":[52,66],"losses":[53],"issued":[55],"loans.":[56],"These":[57],"applications":[60],"may":[61],"never":[62],"achieve":[63],"full":[65],"without":[67],"semantic":[69,87],"context":[70,105],"data.":[73],"A":[74],"knowledge":[75,120,137],"graph":[76,121,138],"a":[78,113],"collection":[79],"linked":[81],"entities":[82],"objects":[84],"that":[85,135],"include":[86],"information":[88],"contextualize":[90],"them.":[91],"Knowledge":[92],"graphs":[93],"allow":[94],"machines":[95],"incorporate":[97],"human":[98],"expertise":[99],"into":[100],"decision-making":[102],"provide":[104],"applications.":[109],"Therefore,":[110],"we":[111],"proposed":[112],"prediction":[116,126],"model":[117],"based":[118],"technology":[122],"improve":[124],"model's":[127],"accuracy":[128],"interpretability.":[130],"The":[131],"experimental":[132],"results":[133],"demonstrated":[134],"incorporating":[136],"embedding":[139],"features":[141],"can":[142],"boost":[143],"performance":[145],"conventional":[148],"classifiers":[151],"risk.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}