{"id":"https://openalex.org/W7224801784","doi":"https://doi.org/10.31098/quant.4745","title":"Predicting Loan Default Among Borrowers Using Bootstrapped Digital Lending Platforms in Metro Manila, Philippines: A Survey-Based Gradient Boosting Approach","display_name":"Predicting Loan Default Among Borrowers Using Bootstrapped Digital Lending Platforms in Metro Manila, Philippines: A Survey-Based Gradient Boosting Approach","publication_year":2026,"publication_date":"2026-10-30","ids":{"openalex":"https://openalex.org/W7224801784","doi":"https://doi.org/10.31098/quant.4745"},"language":"en","primary_location":{"id":"doi:10.31098/quant.4745","doi":"https://doi.org/10.31098/quant.4745","is_oa":true,"landing_page_url":"https://doi.org/10.31098/quant.4745","pdf_url":"https://journals.researchsynergypress.com/index.php/aqa/article/download/4745/2409","source":{"id":"https://openalex.org/S4210198410","display_name":"Applied Quantitative Analysis","issn_l":"2808-4640","issn":["2808-4640","2808-4934"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Quantitative Analysis","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://journals.researchsynergypress.com/index.php/aqa/article/download/4745/2409","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034830311","display_name":"Neil T. Awit","orcid":"https://orcid.org/0009-0008-4413-2300","observed_orcids":["https://orcid.org/0009-0008-4413-2300"]},"institutions":[{"id":"https://openalex.org/I2800655693","display_name":"Lyceum of the Philippines University","ror":"https://ror.org/027e56k73","country_code":"PH","type":"education","lineage":["https://openalex.org/I2800655693"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Neil T Awit","raw_affiliation_strings":["Lyceum of the Philippines University"],"raw_orcid":"https://orcid.org/0009-0008-4413-2300","affiliations":[{"raw_affiliation_string":"Lyceum of the Philippines University","institution_ids":["https://openalex.org/I2800655693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117865416","display_name":"Allan Calderon","orcid":"https://orcid.org/0009-0002-2764-0801","observed_orcids":["https://orcid.org/0009-0002-2764-0801"]},"institutions":[{"id":"https://openalex.org/I2800655693","display_name":"Lyceum of the Philippines University","ror":"https://ror.org/027e56k73","country_code":"PH","type":"education","lineage":["https://openalex.org/I2800655693"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Allan A Calderon","raw_affiliation_strings":["Lyceum of the Philippines University"],"raw_orcid":"https://orcid.org/0009-0002-2764-0801","affiliations":[{"raw_affiliation_string":"Lyceum of the Philippines University","institution_ids":["https://openalex.org/I2800655693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007983283","display_name":"Emmanuel J. Dotong","orcid":"https://orcid.org/0000-0002-7290-0767","observed_orcids":["https://orcid.org/0000-0002-7290-0767"]},"institutions":[{"id":"https://openalex.org/I5996616","display_name":"De La Salle University","ror":"https://ror.org/04xftk194","country_code":"PH","type":"education","lineage":["https://openalex.org/I4405258692","https://openalex.org/I5996616"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Emmanuel J Dotong","raw_affiliation_strings":["De La Salle University"],"raw_orcid":"https://orcid.org/0000-0002-7290-0767","affiliations":[{"raw_affiliation_string":"De La Salle University","institution_ids":["https://openalex.org/I5996616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":"6","issue":"2","first_page":"137","last_page":"151"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9653000235557556,"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":0.9653000235557556,"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/T11995","display_name":"FinTech, Crowdfunding, Digital Finance","score":0.01860000006854534,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"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/T10987","display_name":"Microfinance and Financial Inclusion","score":0.012000000104308128,"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/loan-default-prediction","display_name":"loan default prediction","score":0.9599999785423279},{"id":"https://openalex.org/keywords/credit-risk-assessment","display_name":"credit risk assessment","score":0.8119999766349792},{"id":"https://openalex.org/keywords/catboost","display_name":"CatBoost","score":0.8130000233650208},{"id":"https://openalex.org/keywords/shap","display_name":"SHAP","score":0.7699999809265137},{"id":"https://openalex.org/keywords/loan-size","display_name":"loan size","score":0.859000027179718},{"id":"https://openalex.org/keywords/microfinance-borrowers","display_name":"microfinance borrowers","score":0.5009999871253967},{"id":"https://openalex.org/keywords/metro-manila","display_name":"Metro Manila","score":0.9359999895095825}],"concepts":[{"id":"https://openalex.org/C2777764128","wikidata":"https://www.wikidata.org/wiki/Q189539","display_name":"Loan","level":2,"score":0.7950999736785889},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.6183000206947327},{"id":"https://openalex.org/C69637215","wikidata":"https://www.wikidata.org/wiki/Q702362","display_name":"Default","level":2,"score":0.5929999947547913},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5727999806404114},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5536999702453613},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.49570000171661377},{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.46000000834465027},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4246000051498413},{"id":"https://openalex.org/C198477413","wikidata":"https://www.wikidata.org/wiki/Q7647069","display_name":"Survey data collection","level":2,"score":0.400299996137619},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.382999986410141},{"id":"https://openalex.org/C158502994","wikidata":"https://www.wikidata.org/wiki/Q7702559","display_name":"Term loan","level":5,"score":0.3619999885559082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34779998660087585},{"id":"https://openalex.org/C139043278","wikidata":"https://www.wikidata.org/wiki/Q837171","display_name":"Financial services","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.3452000021934509},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3303000032901764},{"id":"https://openalex.org/C71387314","wikidata":"https://www.wikidata.org/wiki/Q494128","display_name":"Non-performing loan","level":3,"score":0.3276999890804291},{"id":"https://openalex.org/C2779806880","wikidata":"https://www.wikidata.org/wiki/Q778470","display_name":"Probability of default","level":3,"score":0.29339998960494995},{"id":"https://openalex.org/C2777138686","wikidata":"https://www.wikidata.org/wiki/Q1787103","display_name":"Credit score","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C51034333","wikidata":"https://www.wikidata.org/wiki/Q4747796","display_name":"Amortizing loan","level":5,"score":0.2651999890804291}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.31098/quant.4745","doi":"https://doi.org/10.31098/quant.4745","is_oa":true,"landing_page_url":"https://doi.org/10.31098/quant.4745","pdf_url":"https://journals.researchsynergypress.com/index.php/aqa/article/download/4745/2409","source":{"id":"https://openalex.org/S4210198410","display_name":"Applied Quantitative Analysis","issn_l":"2808-4640","issn":["2808-4640","2808-4934"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Quantitative Analysis","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.31098/quant.4745","doi":"https://doi.org/10.31098/quant.4745","is_oa":true,"landing_page_url":"https://doi.org/10.31098/quant.4745","pdf_url":"https://journals.researchsynergypress.com/index.php/aqa/article/download/4745/2409","source":{"id":"https://openalex.org/S4210198410","display_name":"Applied Quantitative Analysis","issn_l":"2808-4640","issn":["2808-4640","2808-4934"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Quantitative Analysis","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[{"id":"https://openalex.org/study-designs/observational-study","display_name":"Observational Study"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224801784.pdf","grobid_xml":"https://content.openalex.org/works/W7224801784.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W2185712725","https://openalex.org/W2899422772","https://openalex.org/W2903172129","https://openalex.org/W3013460382","https://openalex.org/W3125279366","https://openalex.org/W3179103254","https://openalex.org/W3185193282","https://openalex.org/W3211183921","https://openalex.org/W4213064715","https://openalex.org/W4285154599","https://openalex.org/W4327808510","https://openalex.org/W4416906016"],"related_works":["https://openalex.org/W7161274900","https://openalex.org/W4415267677","https://openalex.org/W7124127811","https://openalex.org/W7161364277","https://openalex.org/W4248788981","https://openalex.org/W4413738030","https://openalex.org/W4410427859","https://openalex.org/W3212443433","https://openalex.org/W7130400105","https://openalex.org/W4417521497"],"abstract_inverted_index":{"This":[0],"study":[1],"developed":[2],"a":[3,25,61],"predictive":[4],"model":[5],"of":[6,92,132,145],"loan":[7,51,99,111],"default":[8,119],"among":[9,150],"512":[10],"borrowers":[11],"using":[12,24],"bootstrapped":[13,40,151],"digital":[14,41,152],"lending":[15,42,153],"platforms":[16,43],"in":[17,142],"Metro":[18],"Manila,":[19],"Philippines.":[20],"Data":[21],"were":[22,35,80,113,140],"collected":[23],"validated":[26],"survey":[27,56],"instrument":[28],"via":[29],"quota-controlled":[30],"stratified":[31],"random":[32],"sampling.":[33],"Quotas":[34],"allocated":[36],"based":[37],"on":[38,68],"the":[39,69,84,93,133,143],"respondents":[44],"used.":[45],"CatBoost":[46],"was":[47],"used":[48,81],"to":[49,82],"predict":[50],"repayment":[52],"outcomes":[53],"from":[54],"self-reported":[55],"data.":[57],"Model":[58],"evaluation":[59],"employed":[60],"70/30":[62],"training-test":[63],"split":[64],"and":[65,75,123,130],"5-fold":[66],"cross-validation":[67],"full":[70],"dataset.":[71],"Feature":[72],"importance":[73],"analysis":[74,106],"SHapley":[76],"Additive":[77],"exPlanations":[78],"(SHAP)":[79],"interpret":[83],"model's":[85,94],"predictions.":[86],"Loan":[87],"characteristics":[88],"accounted":[89,127],"for":[90,103,128],"90.81%":[91],"reported":[95,134],"feature":[96,135],"importance,":[97,136],"with":[98,116],"amount":[100],"alone":[101],"accounting":[102],"82.85%.":[104],"SHAP":[105],"further":[107],"indicated":[108],"that":[109],"higher":[110,117],"amounts":[112],"generally":[114],"associated":[115],"predicted":[118],"risk.":[120],"Behavioral":[121],"traits":[122],"financial":[124],"capacity":[125],"indicators":[126],"2.91%":[129],"6.28%":[131],"respectively.":[137],"These":[138],"findings":[139],"leveraged":[141],"development":[144],"credit":[146],"risk":[147],"assessment":[148],"practices":[149],"platforms.":[154]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-10-31T00:00:00"}
