{"id":"https://openalex.org/W7204237025","doi":"https://doi.org/10.47709/cnahpc.v8i3.9459","title":"Analysis Of The Determinants Of Financial Resilience Among Retiree Customers Using An Explainable Ai (Xai) Approach","display_name":"Analysis Of The Determinants Of Financial Resilience Among Retiree Customers Using An Explainable Ai (Xai) Approach","publication_year":2026,"publication_date":"2026-08-03","ids":{"openalex":"https://openalex.org/W7204237025","doi":"https://doi.org/10.47709/cnahpc.v8i3.9459"},"language":"en","primary_location":{"id":"doi:10.47709/cnahpc.v8i3.9459","doi":"https://doi.org/10.47709/cnahpc.v8i3.9459","is_oa":true,"landing_page_url":"https://doi.org/10.47709/cnahpc.v8i3.9459","pdf_url":"https://jurnal.itscience.org/index.php/CNAPC/article/download/9459/6302","source":{"id":"https://openalex.org/S4210215736","display_name":"Journal Of Computer Networks Architecture and High Performance Computing","issn_l":"2655-9102","issn":["2655-9102"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Networks, Architecture and High Performance Computing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://jurnal.itscience.org/index.php/CNAPC/article/download/9459/6302","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049496970","display_name":"Victor Saputra Ginting","orcid":"https://orcid.org/0000-0001-9978-4930","observed_orcids":["https://orcid.org/0000-0001-9978-4930"]},"institutions":[{"id":"https://openalex.org/I4405273711","display_name":"Universitas Deli Sumatera","ror":"https://ror.org/00b1tq324","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405273711"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Victor Saputra Ginting","raw_affiliation_strings":["Universitas Deli Sumatera"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Deli Sumatera","institution_ids":["https://openalex.org/I4405273711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093755491","display_name":"Rahmatika Hizria","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405273711","display_name":"Universitas Deli Sumatera","ror":"https://ror.org/00b1tq324","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405273711"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Rahmatika Hizria","raw_affiliation_strings":["Universitas Deli Sumatera"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Deli Sumatera","institution_ids":["https://openalex.org/I4405273711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058424066","display_name":"Said Hambali Takhir","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405273711","display_name":"Universitas Deli Sumatera","ror":"https://ror.org/00b1tq324","country_code":"ID","type":"education","lineage":["https://openalex.org/I4405273711"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Said Hambali Takhir","raw_affiliation_strings":["Universitas Deli Sumatera"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Deli Sumatera","institution_ids":["https://openalex.org/I4405273711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405273711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"3","first_page":"493","last_page":"503"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9810000061988831,"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":0.9810000061988831,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.005100000184029341,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.002300000051036477,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/financial-resilience","display_name":"financial resilience","score":0.9980000257492065},{"id":"https://openalex.org/keywords/retirees","display_name":"retirees","score":0.8519999980926514},{"id":"https://openalex.org/keywords/credit-risk-management","display_name":"credit risk management","score":0.9440000057220459},{"id":"https://openalex.org/keywords/credit-scoring","display_name":"credit scoring","score":0.6330000162124634},{"id":"https://openalex.org/keywords/explainable-ai","display_name":"explainable AI","score":0.7940000295639038},{"id":"https://openalex.org/keywords/shap","display_name":"SHAP","score":0.9710000157356262},{"id":"https://openalex.org/keywords/loan-delinquency","display_name":"loan delinquency","score":0.8050000071525574},{"id":"https://openalex.org/keywords/debt-to-income-ratio","display_name":"debt-to-income ratio","score":0.9909999966621399},{"id":"https://openalex.org/keywords/credit-scores","display_name":"credit scores","score":0.8349999785423279},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.5809999704360962},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.4950000047683716},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.625},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8560000061988831},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.9440000057220459}],"concepts":[{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.7218999862670898},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.6450999975204468},{"id":"https://openalex.org/C2777764128","wikidata":"https://www.wikidata.org/wiki/Q189539","display_name":"Loan","level":2,"score":0.5622000098228455},{"id":"https://openalex.org/C137176749","wikidata":"https://www.wikidata.org/wiki/Q4105337","display_name":"Psychological resilience","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C2983355114","wikidata":"https://www.wikidata.org/wiki/Q161380","display_name":"Credit card","level":3,"score":0.4950999915599823},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.4659999907016754},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.40540000796318054},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.39969998598098755},{"id":"https://openalex.org/C138262166","wikidata":"https://www.wikidata.org/wiki/Q570938","display_name":"Net income","level":2,"score":0.3716999888420105},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C2778770122","wikidata":"https://www.wikidata.org/wiki/Q1933764","display_name":"Net worth","level":3,"score":0.36079999804496765},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.3580999970436096},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.34439998865127563},{"id":"https://openalex.org/C49898467","wikidata":"https://www.wikidata.org/wiki/Q1517706","display_name":"Stratified sampling","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C2777138686","wikidata":"https://www.wikidata.org/wiki/Q1787103","display_name":"Credit score","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.32339999079704285},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31839999556541443},{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C68842666","wikidata":"https://www.wikidata.org/wiki/Q1070699","display_name":"Credit history","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C139043278","wikidata":"https://www.wikidata.org/wiki/Q837171","display_name":"Financial services","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.26809999346733093},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C189326681","wikidata":"https://www.wikidata.org/wiki/Q10294","display_name":"Poverty","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.47709/cnahpc.v8i3.9459","doi":"https://doi.org/10.47709/cnahpc.v8i3.9459","is_oa":true,"landing_page_url":"https://doi.org/10.47709/cnahpc.v8i3.9459","pdf_url":"https://jurnal.itscience.org/index.php/CNAPC/article/download/9459/6302","source":{"id":"https://openalex.org/S4210215736","display_name":"Journal Of Computer Networks Architecture and High Performance Computing","issn_l":"2655-9102","issn":["2655-9102"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Networks, Architecture and High Performance Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.47709/cnahpc.v8i3.9459","doi":"https://doi.org/10.47709/cnahpc.v8i3.9459","is_oa":true,"landing_page_url":"https://doi.org/10.47709/cnahpc.v8i3.9459","pdf_url":"https://jurnal.itscience.org/index.php/CNAPC/article/download/9459/6302","source":{"id":"https://openalex.org/S4210215736","display_name":"Journal Of Computer Networks Architecture and High Performance Computing","issn_l":"2655-9102","issn":["2655-9102"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Networks, Architecture and High Performance Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204237025.pdf","grobid_xml":"https://content.openalex.org/works/W7204237025.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W4411142500","https://openalex.org/W4416122040","https://openalex.org/W4416414587"],"related_works":["https://openalex.org/W4412718571","https://openalex.org/W7215572657","https://openalex.org/W4416248840","https://openalex.org/W4410036387","https://openalex.org/W7134973532","https://openalex.org/W7214296168","https://openalex.org/W7133127479","https://openalex.org/W4402596900","https://openalex.org/W7143477763","https://openalex.org/W4417509663"],"abstract_inverted_index":{"Financial":[0],"resilience":[1,58,82,160],"among":[2,112],"high-risk":[3],"retiree":[4],"customer":[5],"segments":[6],"is":[7],"a":[8,39,46,52,109,173,188],"crucial":[9],"issue":[10],"in":[11,23,83],"credit":[12,178,192],"risk":[13],"management,":[14],"particularly":[15],"because":[16],"traditional":[17],"scoring":[18],"models":[19],"are":[20],"often":[21],"black-box":[22],"nature":[24],"and":[25,34,65,76,100,117,141,172,190],"fail":[26],"to":[27,50,67,74,103,126,198],"provide":[28,187],"transparent":[29,189],"insight":[30],"into":[31],"the":[32,78,94,128,132,147,155,162],"economic":[33],"behavioral":[35],"factors":[36],"that":[37,122,154],"influence":[38],"borrower's":[40],"repayment":[41,210],"capacity.":[42],"This":[43],"research":[44,88],"pursues":[45],"dual":[47],"objective:":[48],"first,":[49],"develop":[51],"high-performing":[53],"predictive":[54],"model":[55,130],"for":[56,146],"financial":[57,159,196],"classification":[59],"using":[60],"ensemble":[61],"Machine":[62],"Learning":[63],"methods,":[64],"second,":[66],"apply":[68],"SHAP-based":[69],"Explainable":[70],"AI":[71],"(XAI)":[72],"techniques":[73],"identify":[75],"quantify":[77],"key":[79],"determinants":[80,157],"of":[81,139,144,164],"an":[84,137,142],"accountable":[85],"manner.":[86],"The":[87,119],"methodology":[89],"involved":[90],"processing":[91],"data":[92],"from":[93],"Kaggle":[95],"platform,":[96],"including":[97],"stratified":[98],"sampling":[99],"SMOTE":[101],"oversampling":[102],"address":[104],"class":[105],"imbalance,":[106],"along":[107],"with":[108,177],"performance":[110],"comparison":[111],"Logistic":[113,123],"Regression,":[114],"Random":[115],"Forest,":[116],"XGBoost.":[118],"results":[120],"show":[121],"Regression":[124],"proved":[125],"be":[127],"best-performing":[129],"on":[131],"held-out":[133],"test":[134],"set,":[135],"achieving":[136],"AUC":[138],"0.9479":[140],"F1-Score":[143],"0.7313":[145],"resilient":[148],"class.":[149],"Furthermore,":[150],"SHAP":[151],"analysis":[152],"revealed":[153],"strongest":[156],"driving":[158],"were":[161],"number":[163],"prior":[165],"delinquencies,":[166],"loan":[167],"purpose":[168],"(particularly":[169],"business-purpose":[170],"loans),":[171],"low":[174],"debt-to-income":[175],"ratio,":[176],"score":[179],"also":[180],"contributing.":[181],"In":[182],"practical":[183],"terms,":[184],"these":[185],"findings":[186],"humane":[191],"assessment":[193],"framework,":[194],"enabling":[195],"institutions":[197],"formulate":[199],"more":[200],"inclusive":[201],"yet":[202],"prudent":[203],"lending":[204],"policies":[205],"by":[206],"prioritizing":[207],"customers'":[208],"actual":[209],"capacity":[211],"over":[212],"age":[213],"alone.":[214]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-08-27T00:00:00"}
