{"id":"https://openalex.org/W4391114264","doi":"https://doi.org/10.25300/misq/2022/17491","title":"Depicting Risk Profile over Time: A Novel Multiperiod Loan Default Prediction Approach","display_name":"Depicting Risk Profile over Time: A Novel Multiperiod Loan Default Prediction Approach","publication_year":2023,"publication_date":"2023-12-01","ids":{"openalex":"https://openalex.org/W4391114264","doi":"https://doi.org/10.25300/misq/2022/17491"},"language":"en","primary_location":{"id":"doi:10.25300/misq/2022/17491","is_oa":false,"landing_page_url":"https://doi.org/10.25300/misq/2022/17491","pdf_url":null,"source":{"id":"https://openalex.org/S57293258","display_name":"MIS Quarterly","issn_l":"0276-7783","issn":["0276-7783","2162-9730"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4327875293","host_organization_name":"MIS Quarterly","host_organization_lineage":["https://openalex.org/P4327875293"],"host_organization_lineage_names":["MIS Quarterly"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MIS Quarterly","raw_type":"journal-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/A5101646633","display_name":"Zhao Wang","orcid":"https://orcid.org/0000-0002-3352-3655"},"institutions":[{"id":"https://openalex.org/I39774598","display_name":"Hefei University","ror":"https://ror.org/01f5rdf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I39774598"]},{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhao Wang","raw_affiliation_strings":["School of Management, Hefei University of Technology, The Philosophy and Social Sciences Key Laboratory of Digital Economy and Smart Enterprise Management, Anhui Province, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Management, Hefei University of Technology, The Philosophy and Social Sciences Key Laboratory of Digital Economy and Smart Enterprise Management, Anhui Province, Hefei, China","institution_ids":["https://openalex.org/I16365422","https://openalex.org/I39774598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023611552","display_name":"Cuiqing Jiang","orcid":"https://orcid.org/0000-0001-6492-4550"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cuiqing Jiang","raw_affiliation_strings":["School of Management, Hefei University of Technology, The Philosophy and Social Sciences Laboratory of Data Science and Intelligent Society Governance, Ministry of Education, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Management, Hefei University of Technology, The Philosophy and Social Sciences Laboratory of Data Science and Intelligent Society Governance, Ministry of Education, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015735678","display_name":"Huimin Zhao","orcid":"https://orcid.org/0000-0002-6471-9837"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huimin Zhao","raw_affiliation_strings":["Sheldon B. Lubar College of Business, University of Wisconsin\u2013Milwaukee, Milwaukee, WI, U.S.A"],"affiliations":[{"raw_affiliation_string":"Sheldon B. Lubar College of Business, University of Wisconsin\u2013Milwaukee, Milwaukee, WI, U.S.A","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101646633"],"corresponding_institution_ids":["https://openalex.org/I16365422","https://openalex.org/I39774598"],"apc_list":null,"apc_paid":null,"fwci":7.1217,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.97004915,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"47","issue":"4","first_page":"1455","last_page":"1486"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9962999820709229,"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":0.9962999820709229,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.676872730255127},{"id":"https://openalex.org/keywords/loss-given-default","display_name":"Loss given default","score":0.6347863078117371},{"id":"https://openalex.org/keywords/probability-of-default","display_name":"Probability of default","score":0.6255965232849121},{"id":"https://openalex.org/keywords/credit-risk","display_name":"Credit risk","score":0.6005244851112366},{"id":"https://openalex.org/keywords/default","display_name":"Default","score":0.5515727996826172},{"id":"https://openalex.org/keywords/loan","display_name":"Loan","score":0.5296656489372253},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5128312706947327},{"id":"https://openalex.org/keywords/profitability-index","display_name":"Profitability index","score":0.47029635310173035},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.44537192583084106},{"id":"https://openalex.org/keywords/identifiability","display_name":"Identifiability","score":0.4208466708660126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3780551552772522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34566202759742737},{"id":"https://openalex.org/keywords/actuarial-science","display_name":"Actuarial science","score":0.31549501419067383},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.2081969976425171},{"id":"https://openalex.org/keywords/capital-requirement","display_name":"Capital requirement","score":0.17906898260116577},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.15143826603889465},{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.09671935439109802}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.676872730255127},{"id":"https://openalex.org/C133930124","wikidata":"https://www.wikidata.org/wiki/Q1460730","display_name":"Loss given default","level":4,"score":0.6347863078117371},{"id":"https://openalex.org/C2779806880","wikidata":"https://www.wikidata.org/wiki/Q778470","display_name":"Probability of default","level":3,"score":0.6255965232849121},{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.6005244851112366},{"id":"https://openalex.org/C69637215","wikidata":"https://www.wikidata.org/wiki/Q702362","display_name":"Default","level":2,"score":0.5515727996826172},{"id":"https://openalex.org/C2777764128","wikidata":"https://www.wikidata.org/wiki/Q189539","display_name":"Loan","level":2,"score":0.5296656489372253},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5128312706947327},{"id":"https://openalex.org/C129361004","wikidata":"https://www.wikidata.org/wiki/Q2470236","display_name":"Profitability index","level":2,"score":0.47029635310173035},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.44537192583084106},{"id":"https://openalex.org/C122770356","wikidata":"https://www.wikidata.org/wiki/Q1656753","display_name":"Identifiability","level":2,"score":0.4208466708660126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3780551552772522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34566202759742737},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.31549501419067383},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.2081969976425171},{"id":"https://openalex.org/C2864544","wikidata":"https://www.wikidata.org/wiki/Q2914988","display_name":"Capital requirement","level":3,"score":0.17906898260116577},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.15143826603889465},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.09671935439109802},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.25300/misq/2022/17491","is_oa":false,"landing_page_url":"https://doi.org/10.25300/misq/2022/17491","pdf_url":null,"source":{"id":"https://openalex.org/S57293258","display_name":"MIS Quarterly","issn_l":"0276-7783","issn":["0276-7783","2162-9730"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4327875293","host_organization_name":"MIS Quarterly","host_organization_lineage":["https://openalex.org/P4327875293"],"host_organization_lineage_names":["MIS Quarterly"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MIS Quarterly","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1276866904","https://openalex.org/W1501960888","https://openalex.org/W1836875240","https://openalex.org/W2003119650","https://openalex.org/W2043324736","https://openalex.org/W2064065622","https://openalex.org/W2068911395","https://openalex.org/W2131816657","https://openalex.org/W2137959503","https://openalex.org/W2297389033","https://openalex.org/W2300875245","https://openalex.org/W2305849921","https://openalex.org/W2314110168","https://openalex.org/W2358113125","https://openalex.org/W2466279936","https://openalex.org/W2506619760","https://openalex.org/W2555763236","https://openalex.org/W2562923621","https://openalex.org/W2563585333","https://openalex.org/W2578336118","https://openalex.org/W2747436277","https://openalex.org/W2804045672","https://openalex.org/W2913196994","https://openalex.org/W2914424339","https://openalex.org/W2963232127","https://openalex.org/W3009205158","https://openalex.org/W3035198387","https://openalex.org/W3045116697","https://openalex.org/W3122953116","https://openalex.org/W3125615501","https://openalex.org/W3128206571","https://openalex.org/W3133916247","https://openalex.org/W3153557772","https://openalex.org/W4200286225"],"related_works":["https://openalex.org/W2187783179","https://openalex.org/W1994927285","https://openalex.org/W2081577806","https://openalex.org/W2262093139","https://openalex.org/W3124496798","https://openalex.org/W3121237533","https://openalex.org/W4401116089","https://openalex.org/W4322722344","https://openalex.org/W114781066","https://openalex.org/W3125376146"],"abstract_inverted_index":{"With":[0],"the":[1,6,47,117,135,143,163,175],"rapid":[2],"development":[3],"of":[4,112,119],"fintech,":[5],"need":[7],"for":[8,33],"dynamic":[9],"credit":[10,21],"risk":[11,41],"evaluation":[12],"is":[13],"becoming":[14],"increasingly":[15],"important.":[16],"While":[17],"previous":[18],"studies":[19],"on":[20,26,183],"scoring":[22,70],"have":[23],"mostly":[24],"focused":[25],"single-period":[27],"loan":[28,205],"default":[29,37,55,86,90,95,113,120,130,136],"prediction,":[30],"we":[31,62,126],"call":[32],"a":[34,64,74,83,89,94,104,128],"new":[35],"avenue\u2014multiperiod":[36],"prediction":[38,57,146],"(MPDP)\u2014to":[39],"depict":[40],"profiles":[42],"over":[43,122],"time.":[44],"To":[45,107],"address":[46],"challenges":[48],"raised":[49],"by":[50],"MPDP,":[51],"such":[52],"as":[53,157,159],"monotonic":[54],"probability":[56,121],"and":[58,68,81,93,100,115,148,151,154,167,179,192,196,203],"complex":[59],"relationship":[60],"accommodation,":[61],"propose":[63,127],"novel":[65],"approach,":[66],"hybrid":[67,75],"collective":[69],"(HACS).":[71],"We":[72],"design":[73],"modeling":[76,131],"strategy":[77],"to":[78,133],"predict":[79,190],"whether":[80],"when":[82],"borrower":[84],"will":[85],"separately":[87],"through":[88,103],"discrimination":[91,149],"model":[92,144],"time":[96,114,124,137],"estimation":[97,138],"model,":[98],"respectively,":[99],"synthesize":[101],"them":[102],"probabilistic":[105],"framework.":[106],"accommodate":[108],"various":[109],"possible":[110],"patterns":[111],"measure":[116],"distribution":[118],"successive":[123],"intervals,":[125],"joint":[129],"method":[132],"train":[134],"model.":[139],"Empirical":[140],"evaluations":[141],"at":[142,162],"(time-to-default":[145],"performance":[147,166],"performance)":[150,169],"mechanism":[152],"(identifiability":[153],"discriminability)":[155],"levels,":[156],"well":[158],"impact":[160],"analyses":[161],"application":[164],"(granting":[165],"profitability":[168],"level,":[170],"show":[171],"that":[172],"HACS":[173],"outperforms":[174],"benchmarked":[176],"survival":[177],"analysis":[178],"multilabel":[180],"learning":[181],"methods":[182],"all":[184],"fronts.":[185],"It":[186],"can":[187],"more":[188],"accurately":[189],"time-to-default":[191],"provide":[193],"financial":[194],"institutions":[195],"investors":[197],"better":[198],"decision-support":[199],"in":[200],"granting":[201],"loans":[202],"selecting":[204],"portfolios.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-22T08:38:42.863108","created_date":"2025-10-10T00:00:00"}