{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T16:26:10Z","timestamp":1773073570641,"version":"3.50.1"},"reference-count":111,"publisher":"Emerald","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,14]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>The crux of this paper is to unveil efficient features and practical tools that can predict credit default.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>The study\u2019s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Research limitations\/implications<\/jats:title>\n                    <jats:p>Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/value<\/jats:title>\n                    <jats:p>This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN\u2019s superior accuracy over LR and suggesting future research directions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1108\/k-09-2023-1888","type":"journal-article","created":{"date-parts":[[2024,4,17]],"date-time":"2024-04-17T00:23:54Z","timestamp":1713313434000},"page":"4709-4733","source":"Crossref","is-referenced-by-count":3,"title":["Default prediction modeling (DPM) with machine learning algorithms: case of non-financial listed companies in Pakistan"],"prefix":"10.1108","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9145-6545","authenticated-orcid":true,"given":"Jahanzaib","family":"Alvi","sequence":"first","affiliation":[{"name":"IQRA University Department of Business Administration, , ,","place":["Karachi, Pakistan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0102-5870","authenticated-orcid":true,"given":"Imtiaz","family":"Arif","sequence":"additional","affiliation":[{"name":"IQRA University Department of Business Administration, , ,","place":["Karachi, Pakistan"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2024,4,17]]},"reference":[{"issue":"4","key":"2026030906372871500_ref001","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1108\/jabes-11-2020-0128","article-title":"The implication of machine learning for financial solvency prediction: an empirical analysis on public listed companies of Bangladesh","volume":"28","author":"Abdullah","year":"2021","journal-title":"Journal of Asian Business and Economic Studies"},{"issue":"8","key":"2026030906372871500_ref002","doi-asserted-by":"publisher","first-page":"1541","DOI":"10.1016\/j.jbankfin.2007.07.014","article-title":"Comparing the performance of market-based and accounting-based bankruptcy prediction models","volume":"32","author":"Agarwal","year":"2008","journal-title":"Journal of Banking and Finance"},{"key":"2026030906372871500_ref003","doi-asserted-by":"publisher","DOI":"10.1016\/j.adiac.2021.100513","article-title":"A horse race of models and estimation methods for predicting bankruptcy","volume":"52","author":"Almaskati","year":"2021","journal-title":"Advances in Accounting"},{"issue":"4","key":"2026030906372871500_ref004","doi-asserted-by":"publisher","first-page":"189","DOI":"10.2307\/2978933","article-title":"Financial ratios, discriminant analysis and the prediction of corporate bankruptcy","volume":"23","author":"Altman","year":"1968","journal-title":"The Journal of Finance"},{"issue":"2","key":"2026030906372871500_ref005","doi-asserted-by":"crossref","DOI":"10.29145\/jqm.0702.02","article-title":"Unraveling the mystery of default prediction: a study on the textile industry in Pakistan","volume":"7","author":"Alvi","year":"2023","journal-title":"Journal of Quantitative Methods"},{"key":"2026030906372871500_ref006","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1016\/j.jebo.2021.01.014","article-title":"Predicting bankruptcy of local government: a machine learning approach","volume":"183","author":"Antulov-Fantulin","year":"2021","journal-title":"Journal of Economic Behavior and Organization"},{"key":"2026030906372871500_ref007","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105936","article-title":"A Bolasso based consistent feature selection enabled random forest classification algorithm: an application to credit risk assessment","volume":"86","author":"Arora","year":"2020","journal-title":"Applied Soft Computing Journal"},{"key":"2026030906372871500_ref008","doi-asserted-by":"publisher","first-page":"416","DOI":"10.1109\/ISS1.2017.8389442","article-title":"Prediction of loan status in commercial bank using machine learning classifier","author":"Arutjothi","year":"2018"},{"key":"2026030906372871500_ref009","doi-asserted-by":"publisher","DOI":"10.3386\/w24506","volume-title":"Sovereign Credit Risk and Exchange Rates: Evidence from CDS Quanto Spreads","author":"Augustin","year":"2018"},{"key":"2026030906372871500_ref010","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/03610918.2021.1910837","article-title":"New metrics and approaches for predicting bankruptcy. Communications in Statistics","author":"Barboza","year":"2021","journal-title":"Simulation and Computation"},{"issue":"1","key":"2026030906372871500_ref011","doi-asserted-by":"publisher","first-page":"432","DOI":"10.1016\/j.jbankfin.2013.12.013","article-title":"Are hazard models superior to traditional bankruptcy prediction approaches? A comprehensive test","volume":"40","author":"Bauer","year":"2014","journal-title":"Journal of Banking and Finance"},{"key":"2026030906372871500_ref012","doi-asserted-by":"publisher","first-page":"71","DOI":"10.2307\/2490171","article-title":"Financial ratios as predictors","volume":"4","author":"Beaver","year":"1966","journal-title":"Journal of Accounting Research"},{"key":"2026030906372871500_ref013","first-page":"1","article-title":"Financial education association A review of bankruptcy prediction studies: 1930 to present","author":"Bellovary","year":"2007","journal-title":"Journal of Financial Education"},{"key":"2026030906372871500_ref014","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2020.112718","article-title":"Exploration of credit risk of P2P platform based on data mining technology","volume":"372","author":"Cai","year":"2020","journal-title":"Journal of Computational and Applied Mathematics"},{"issue":"2","key":"2026030906372871500_ref015","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1007\/s11156-018-0716-7","article-title":"On corporate financial distress prediction: what can we learn from private firms in a developing economy? Evidence from Greece","volume":"52","author":"Charalambakis","year":"2019","journal-title":"Review of Quantitative Finance and Accounting"},{"issue":"9","key":"2026030906372871500_ref016","doi-asserted-by":"publisher","first-page":"1055","DOI":"10.1080\/14697680902814274","article-title":"Predicting bankruptcy using the discrete-time semiparametric hazard model","volume":"10","author":"Cheng","year":"2010","journal-title":"Quantitative Finance"},{"key":"2026030906372871500_ref017","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.eswa.2018.05.026","article-title":"Predicting financial distress of contractors in the construction industry using ensemble learning","volume":"110","author":"Choi","year":"2018","journal-title":"Expert Systems with Applications"},{"issue":"10","key":"2026030906372871500_ref018","doi-asserted-by":"publisher","first-page":"1817","DOI":"10.1080\/01605682.2018.1460017","article-title":"Investigation of financial distress with a dynamic logit based on the linkage between liquidity and profitability status of listed firms","volume":"70","author":"Christopoulos","year":"2019","journal-title":"Journal of the Operational Research Society"},{"issue":"3","key":"2026030906372871500_ref019","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1108\/jfmpc-01-2022-0004","article-title":"Default prediction of small and medium enterprises: portuguese construction sector","volume":"28","author":"Costa","year":"2023","journal-title":"Journal of Financial Management of Property and Construction"},{"key":"2026030906372871500_ref020","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106263","article-title":"Statistical and machine learning models in credit scoring: a systematic literature survey","volume":"91","author":"Dastile","year":"2020","journal-title":"Applied Soft Computing Journal"},{"key":"2026030906372871500_ref021","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/20430795.2021.2017257","article-title":"Application of artificial neural networks in predicting financial distress in the JSE financial services and manufacturing companies","author":"Dube","year":"2021","journal-title":"Journal of Sustainable Finance and Investment"},{"key":"2026030906372871500_ref109","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1016\/j.procs.2022.01.041","article-title":"The impact of ESG factors on the performance of information technology companies","volume":"199","author":"Egorova","year":"2022","journal-title":"Procedia Computer Science"},{"issue":"9","key":"2026030906372871500_ref022","doi-asserted-by":"publisher","first-page":"1101","DOI":"10.1108\/MF-07-2017-0244","article-title":"A three-stage dynamic model of financial distress","volume":"44","author":"Farooq","year":"2018","journal-title":"Managerial Finance"},{"issue":"7","key":"2026030906372871500_ref111","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1002\/for.2588","article-title":"Predicting multistage financial distress: reflections on sampling, feature and model selection criteria","volume":"38","author":"Farooq","year":"2019","journal-title":"Journal of Forecasting"},{"key":"2026030906372871500_ref023","article-title":"Forecasting distress in European SME portfolios","author":"Filipe","year":"2014"},{"issue":"1","key":"2026030906372871500_ref024","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1111\/j.1468-5957.1990.tb00555.x","article-title":"Predicting bankruptcy for firms in financial distress","volume":"17","author":"Gilbert","year":"1990","journal-title":"Journal of Business Finance and Accounting"},{"issue":"6","key":"2026030906372871500_ref025","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1108\/MEDAR-10-2019-0596","article-title":"Investigating risk disclosures in Italian integrated reports","volume":"28","author":"Guthrie","year":"2020","journal-title":"Meditari Accountancy Research"},{"issue":"4","key":"2026030906372871500_ref026","doi-asserted-by":"publisher","first-page":"1163","DOI":"10.1108\/BPMJ-06-2020-0273","article-title":"Corporation financial distress prediction with deep learning: analysis of public listed companies in Malaysia","volume":"27","author":"Halim","year":"2021","journal-title":"Business Process Management Journal"},{"issue":"12","key":"2026030906372871500_ref027","doi-asserted-by":"publisher","first-page":"2286","DOI":"10.1016\/j.peptides.2009.09.004","article-title":"Ghrelin inhibits post-infarct myocardial remodeling and improves cardiac function through anti-inflammation effect","volume":"30","author":"Huang","year":"2009","journal-title":"Peptides"},{"issue":"3","key":"2026030906372871500_ref028","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1108\/jeas-05-2018-0063","article-title":"Forecasting Bankruptcy for organizational sustainability in Pakistan","volume":"35","author":"Inam","year":"2019","journal-title":"Journal of Economic and Administrative Sciences"},{"key":"2026030906372871500_ref029","doi-asserted-by":"publisher","DOI":"10.1108\/cr-05-2023-0110","article-title":"Predicting default risk bancassurance using GMDH and dce-GMDH neural network models","author":"Jaber","year":"2023","journal-title":"Competitiveness Review: An International Business Journal"},{"issue":"4","key":"2026030906372871500_ref030","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1108\/JAAR-07-2017-0070","article-title":"Efficacy of going concern prediction model for creditor oriented regime via liquidation: a MDA approach","volume":"19","author":"Javaid","year":"2018","journal-title":"Journal of Applied Accounting Research"},{"key":"2026030906372871500_ref031","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/j.intfin.2019.03.004","article-title":"Predicting private company failure: a multi-class analysis","volume":"61","author":"Jones","year":"2019","journal-title":"Journal of International Financial Markets, Institutions and Money"},{"issue":"5","key":"2026030906372871500_ref032","doi-asserted-by":"publisher","first-page":"525","DOI":"10.5755\/j01.ee.31.5.25202","article-title":"Cash flows indicators in the prediction of financial distress","volume":"31","author":"Karas","year":"2020","journal-title":"Engineering Economics"},{"issue":"4","key":"2026030906372871500_ref033","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1111\/j.1468-5957.1987.tb00113.x","article-title":"Multivariate normality and forecasting of business bankruptcy","volume":"14","author":"Karels","year":"1987","journal-title":"Journal of Business Finance and Accounting"},{"issue":"3","key":"2026030906372871500_ref034","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1105\/tpc.1.3.351","article-title":"The rice phytochrome gene: structure, autoregulated expression, and binding of GT-1 to a conserved site in the 5\u2019 upstream region","volume":"1","author":"Kay","year":"1989","journal-title":"The Plant Cell"},{"issue":"3","key":"2026030906372871500_ref035","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1007\/s10614-021-10126-5","article-title":"Corporate bankruptcy prediction using machine learning methodologies with a focus on sequential data","volume":"59","author":"Kim","year":"2022","journal-title":"Computational Economics"},{"issue":"3","key":"2026030906372871500_ref036","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1080\/1461670x.2015.1058182","article-title":"Reporting the global financial crisis: a longitudinal tri-nation study of mainstream financial journalism","volume":"18","author":"Knowles","year":"2017","journal-title":"Journalism Studies"},{"issue":"4","key":"2026030906372871500_ref037","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1016\/S0378-4266(86)80003-6","article-title":"An application of the cox proportional hazards model to bank failure","volume":"10","author":"Lane","year":"1986","journal-title":"Journal of Banking and Finance"},{"issue":"4","key":"2026030906372871500_ref038","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1016\/j.csda.2004.11.006","article-title":"Mining the customer credit using classification and regression tree and multivariate adaptive regression splines","volume":"50","author":"Lee","year":"2006","journal-title":"Computational Statistics and Data Analysis"},{"issue":"1-2","key":"2026030906372871500_ref039","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.ins.2008.09.003","article-title":"Gaussian case-based reasoning for business failure prediction with empirical data in China","volume":"179","author":"Li","year":"2009","journal-title":"Information Sciences"},{"issue":"2","key":"2026030906372871500_ref040","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1016\/j.ejor.2016.01.012","article-title":"Financial ratios and corporate governance indicators in bankruptcy prediction: a comprehensive study","volume":"252","author":"Liang","year":"2016","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"2026030906372871500_ref041","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s11573-019-00938-1","article-title":"Bankruptcy prediction and the discriminatory power of annual reports: empirical evidence from financially distressed German companies","volume":"90","author":"Lohmann","year":"2020","journal-title":"Journal of Business Economics"},{"key":"2026030906372871500_ref042","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1017\/CBO9780511753831","volume-title":"Stated Choice Methods: Analysis and Applications","author":"Louviere","year":"2000","edition":"English"},{"key":"2026030906372871500_ref043","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.4131102","article-title":"A bright side of anger: a comprehensive exploration of borrowers\u2019 emotions and credit risk management","author":"Lu","year":"2022","journal-title":"SSRN Electronic Journal"},{"issue":"2","key":"2026030906372871500_ref044","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/exsy.12297","article-title":"A comparison analysis for credit scoring using bagging ensembles","volume":"39","author":"Luo","year":"2022","journal-title":"Expert Systems"},{"issue":"6","key":"2026030906372871500_ref045","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1016\/0305-0483(91)90015-L","article-title":"Survival analysis as a tool for company failure prediction","volume":"19","author":"Luoma","year":"1991","journal-title":"Omega"},{"issue":"1","key":"2026030906372871500_ref046","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899x\/1022\/1\/012042","article-title":"Loan default prediction using decision trees and random forest: a comparative study","volume":"1022","author":"Madaan","year":"2021","journal-title":"IOP Conference Series: Materials Science and Engineering"},{"issue":"1","key":"2026030906372871500_ref047","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1504\/IJBEX.2020.104851","article-title":"An analysis of factors affecting financial distress of airline companies: case of India","volume":"20","author":"Mahtani","year":"2020","journal-title":"International Journal of Business Excellence"},{"key":"2026030906372871500_ref048","doi-asserted-by":"publisher","first-page":"1134","DOI":"10.1016\/j.procs.2020.03.054","article-title":"Predicting financial distress using hybrid feedforward neural network with cuckoo search algorithm","volume":"170","author":"Marso","year":"2020","journal-title":"Procedia Computer Science"},{"issue":"26","key":"2026030906372871500_ref049","doi-asserted-by":"publisher","first-page":"10565","DOI":"10.5897\/ajbm11.1415","article-title":"Developing a business failure prediction model for cooperatives: results of an empirical study in Spain","volume":"5","author":"Mateos-Ronco","year":"2011","journal-title":"African Journal of Business Management"},{"issue":"8","key":"2026030906372871500_ref050","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1108\/01409171211247712","article-title":"Credit risk assessment and the impact of the New Basel Capital Accord on small and medium-sized enterprises: an empirical analysis","volume":"35","author":"Matias Gama","year":"2012","journal-title":"Management Research Review"},{"issue":"4","key":"2026030906372871500_ref051","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1016\/0047-2727(74)90003-6","article-title":"The measurement of urban travel demand","volume":"3","author":"McFadden","year":"1974","journal-title":"Journal of Public Economics"},{"issue":"3","key":"2026030906372871500_ref052","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3390\/ijfs9030039","article-title":"Financial inclusion in emerging economies: the application of machine learning and artificial intelligence in credit risk assessment","volume":"9","author":"Mhlanga","year":"2021","journal-title":"International Journal of Financial Studies"},{"key":"2026030906372871500_ref053","first-page":"99","article-title":"Suggested model for explaining financial distress in Egypt: toward a comprehensive model","author":"Mohamed","year":"2020"},{"key":"2026030906372871500_ref054","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113438","article-title":"The application of PROMETHEE multi-criteria decision aid in financial decision making: case of distress prediction models evaluation","volume":"159","author":"Mousavi","year":"2020","journal-title":"Expert Systems with Applications"},{"key":"2026030906372871500_ref055","author":"Muhammad","year":"2016"},{"key":"2026030906372871500_ref056","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/01605682.2020.1784049","article-title":"Textual analysis and corporate bankruptcy: a financial dictionary-based sentiment approach","author":"Nguyen","year":"2020","journal-title":"Journal of the Operational Research Society"},{"key":"2026030906372871500_ref057","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1109\/ijcnn.1990.137710","article-title":"A neural network model for bankruptcy prediction","author":"Odom","year":"1990"},{"issue":"1","key":"2026030906372871500_ref058","doi-asserted-by":"publisher","first-page":"109","DOI":"10.2307\/2490395","article-title":"Financial ratios and the probabilistic prediction of bankruptcy","volume":"18","author":"Ohlson","year":"1980","journal-title":"Journal of Accounting Research"},{"key":"2026030906372871500_ref059","volume-title":"Predicting Business Failures in Non-Financial Turkish Companies","author":"Okay","year":"2015"},{"issue":"2","key":"2026030906372871500_ref060","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1108\/14720700210430298","article-title":"Corporate governance and corporate failure: a survival analysis. Corporate Governance","volume":"2","author":"Parker","year":"2002","journal-title":"The International Journal of Business in Society"},{"key":"2026030906372871500_ref061","first-page":"2825","article-title":"Scikit-learn: machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"The Journal of Machine Learning Research"},{"key":"2026030906372871500_ref062","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114758","article-title":"A Machine Learning-based DSS for mid and long-term company crisis prediction","volume":"174","author":"Perboli","year":"2021","journal-title":"Expert Systems with Applications"},{"issue":"3","key":"2026030906372871500_ref063","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1016\/j.ijforecast.2019.11.005","article-title":"Predicting bank insolvencies using machine learning techniques","volume":"36","author":"Petropoulos","year":"2020","journal-title":"International Journal of Forecasting"},{"issue":"2","key":"2026030906372871500_ref064","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1108\/AJIM-05-2019-0123","article-title":"Crowdfunding in digital humanities: some evidence from Indonesian social enterprises","volume":"72","author":"Pratono","year":"2020","journal-title":"Aslib Journal of Information Management"},{"issue":"3","key":"2026030906372871500_ref065","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1108\/JAAR-02-2021-0025","article-title":"Non-financial variables related to governance and financial distress prediction in SMEs\u2013evidence from Egypt","volume":"23","author":"Ragab","year":"2021","journal-title":"Journal of Applied Accounting Research"},{"issue":"4","key":"2026030906372871500_ref066","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1111\/j.1468-036x.2006.00330.x","article-title":"Has finance made the world riskier?","volume":"12","author":"Rajan","year":"2006","journal-title":"European Financial Management"},{"issue":"1","key":"2026030906372871500_ref067","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ejor.2006.08.043","article-title":"Bankruptcy prediction in banks and firms via statistical and intelligent techniques \u2013 a review","volume":"180","author":"Ravi Kumar","year":"2007","journal-title":"European Journal of Operational Research"},{"key":"2026030906372871500_ref068","doi-asserted-by":"publisher","DOI":"10.1108\/ijoem-02-2023-0156","article-title":"Drivers of MSME loan defaults using survival analysis: implications for lenders and policy planners","author":"Saha","year":"2023","journal-title":"International Journal of Emerging Markets"},{"issue":"2","key":"2026030906372871500_ref069","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1080\/14697688.2019.1633014","article-title":"Bayesian regularized artificial neural networks for the estimation of the probability of default","volume":"20","author":"Sariev","year":"2020","journal-title":"Quantitative Finance"},{"issue":"51","key":"2026030906372871500_ref070","doi-asserted-by":"publisher","first-page":"5948","DOI":"10.1080\/00036846.2021.1934389","article-title":"Predicting French SME failures: new evidence from machine learning techniques","volume":"53","author":"Schalck","year":"2021","journal-title":"Applied Economics"},{"issue":"17","key":"2026030906372871500_ref110","doi-asserted-by":"crossref","first-page":"14327","DOI":"10.1007\/s00521-022-07472-2","article-title":"Machine learning-driven credit risk: a systemic review","volume":"34","author":"Shi","year":"2022","journal-title":"Neural Computing and Applications"},{"issue":"3","key":"2026030906372871500_ref071","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/s0957-4174(02)00051-9","article-title":"A genetic algorithm application in bankruptcy prediction modeling","volume":"23","author":"Shin","year":"2002","journal-title":"Expert Systems with Applications"},{"issue":"1","key":"2026030906372871500_ref072","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1086\/209665","article-title":"Forecasting bankruptcy more accurately: a simple hazard model","volume":"74","author":"Shumway","year":"2001","journal-title":"Journal of Business"},{"issue":"3","key":"2026030906372871500_ref073","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/S1059-0560(99)00026-X","article-title":"Board structure, ownership, and financial distress in banking firms","volume":"8","author":"Simpson","year":"1999","journal-title":"International Review of Economics and Finance"},{"key":"2026030906372871500_ref074","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1016\/j.ins.2020.03.027","article-title":"Multi-view ensemble learning based on distance-to-model and adaptive clustering for imbalanced credit risk assessment in P2P lending","volume":"525","author":"Song","year":"2020","journal-title":"Information Sciences"},{"key":"2026030906372871500_ref075","first-page":"101","volume-title":"Survey Sampling and Multivariate Analysis for Social Scientists and Engineers","author":"Stopher","year":"1979"},{"issue":"11-12","key":"2026030906372871500_ref076","doi-asserted-by":"publisher","first-page":"1131","DOI":"10.1016\/S0305-0548(99)00149-5","article-title":"Neural network credit scoring models","volume":"27","author":"West","year":"2000","journal-title":"Computers and Operations Research"},{"key":"2026030906372871500_ref112","first-page":"249","article-title":"Weight of evidence: a brief survey","volume":"2","author":"Wod","year":"1985","journal-title":"Bayesian Statistics"},{"issue":"3","key":"2026030906372871500_ref077","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1007\/s11135-010-9376-y","article-title":"Financial distress prediction based on SVM and MDA methods: the case of Chinese listed companies","volume":"45","author":"Xie","year":"2011","journal-title":"Quality and Quantity"},{"issue":"12","key":"2026030906372871500_ref078","doi-asserted-by":"publisher","first-page":"2556","DOI":"10.1016\/j.jss.2010.07.062","article-title":"Two robust remote user authentication protocols using smart cards","volume":"83","author":"Yeh","year":"2010","journal-title":"Journal of Systems and Software"},{"key":"2026030906372871500_ref079","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114840","article-title":"Big data analytics for default prediction using graph theory","volume":"176","author":"Y\u0131ld\u0131r\u0131m","year":"2021","journal-title":"Expert Systems with Applications"},{"key":"2026030906372871500_ref080","doi-asserted-by":"publisher","DOI":"10.1016\/j.elerap.2020.100989","article-title":"Credit risk evaluation model with textual features from loan descriptions for P2P lending","volume":"42","author":"Zhang","year":"2020","journal-title":"Electronic Commerce Research and Applications"},{"key":"2026030906372871500_ref081","doi-asserted-by":"publisher","DOI":"10.1108\/jal-02-2023-0026","article-title":"Liquidity, informational efficiency and firm default risk: a systematic literature review","author":"Zhao","year":"2023","journal-title":"Journal of Accounting Literature"},{"key":"2026030906372871500_ref082","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/1331677X.2020.1867213","article-title":"Feature selection in credit risk modeling: an international evidence","author":"Zhou","year":"2020","journal-title":"Economic Research-Ekonomska Istrazivanja"},{"key":"2026030906372871500_ref083","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1016\/j.procs.2019.12.017","article-title":"A study on predicting loan default based on the random forest algorithm","volume":"162","author":"Zhu","year":"2019","journal-title":"Procedia Computer Science"},{"key":"2026030906372871500_ref084","doi-asserted-by":"publisher","first-page":"59","DOI":"10.2307\/2490859","article-title":"Methodological issues related to the estimation of financial distress prediction models","volume":"22","author":"Zmijewski","year":"1984","journal-title":"Journal of Accounting Research"},{"issue":"1","key":"2026030906372871500_ref085","doi-asserted-by":"publisher","first-page":"99","DOI":"10.17323\/j.jcfr.2073-0438.16.1.2022.99-112","article-title":"Comparative analysis of the predictive power of machine learning models for forecasting the credit ratings of machine-building companies","volume":"16","author":"\u0413\u0440\u0438\u0448\u0443\u043d\u0438\u043d","year":"2022","journal-title":"Journal of Corporate Finance Research\/K\u043e\u0440n\u043e\u0440\u0430mu\u0432\u043d\u044b\u0435 \u0424u\u043d\u0430\u043d\u0441\u044b"},{"issue":"3","key":"2026030906372871500_ref086","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1007\/s00521-012-1017-z","article-title":"Prediction of bankruptcy Iranian corporations through artificial neural network and Probit-based analyses","volume":"23","author":"Ahmadpour Kasgari","year":"2013","journal-title":"Neural Computing and Applications"},{"issue":"4","key":"2026030906372871500_ref087","doi-asserted-by":"publisher","first-page":"7710","DOI":"10.1016\/j.eswa.2008.09.023","article-title":"Alternative diagnosis of corporate bankruptcy: a neuro fuzzy approach","volume":"36","author":"Chen","year":"2009","journal-title":"Expert Systems with Applications"},{"issue":"3","key":"2026030906372871500_ref088","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1108\/maj-05-2016-1371","article-title":"Auditors and early signals of financial distress in local governments","volume":"32","author":"Cohen","year":"2017","journal-title":"Managerial Auditing Journal"},{"issue":"1","key":"2026030906372871500_ref089","doi-asserted-by":"publisher","first-page":"167","DOI":"10.2307\/2490225","article-title":"A discriminant analysis of predictors of business failure","volume":"10","author":"Deakin","year":"1972","journal-title":"Journal of Accounting Research"},{"issue":"6","key":"2026030906372871500_ref091","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1002\/for.1153","article-title":"Business failure prediction using decision trees","volume":"29","author":"Gepp","year":"2010","journal-title":"Journal of Forecasting"},{"key":"2026030906372871500_ref092","first-page":"249","article-title":"Weight of evidence: a brief survey","volume":"2","author":"Good","year":"1985","journal-title":"Bayesian Statistics"},{"key":"2026030906372871500_ref093","first-page":"951","article-title":"NTIRE 2022 challenge on perceptual image quality assessment","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Gu","year":"2022"},{"issue":"1","key":"2026030906372871500_ref094","first-page":"147","article-title":"Estimation capability of financial failures and successes of enterprises using data mining and logistic regression analysis","volume":"16","author":"Kaygin","year":"2016","journal-title":"Ege Academic Review"},{"key":"2026030906372871500_ref095","doi-asserted-by":"publisher","DOI":"10.1016\/j.frl.2021.102046","article-title":"Managers\u2019 loss aversion and firm debt financing: some insights from Vietnamese SMEs","volume":"44","author":"Kim","year":"2022","journal-title":"Finance Research Letters"},{"issue":"4","key":"2026030906372871500_ref096","doi-asserted-by":"publisher","first-page":"775","DOI":"10.24136\/eq.v12i4.40","article-title":"Logit and Probit application for the prediction of bankruptcy in Slovak companies. Equilibrium","volume":"12","author":"Kovacova","year":"2017","journal-title":"Quarterly Journal of Economics and Economic Policy"},{"key":"2026030906372871500_ref097","doi-asserted-by":"crossref","DOI":"10.1108\/S0276-8976(2009)13","volume-title":"Financial Modeling Applications and Data Envelopment Applications","author":"Lawrence","year":"2009"},{"issue":"1","key":"2026030906372871500_ref098","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/0167-9236(96)00018-8","article-title":"Hybrid neural network models for bankruptcy predictions","volume":"18","author":"Lee","year":"1996","journal-title":"Decision Support Systems"},{"key":"2026030906372871500_ref099","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1007\/978-3-642-17254-0_27","volume-title":"Handbook of Computational Finance","author":"Lee","year":"2012"},{"issue":"5","key":"2026030906372871500_ref100","doi-asserted-by":"publisher","first-page":"6244","DOI":"10.1016\/j.eswa.2010.11.043","article-title":"Empirical research of hybridizing principal component analysis with multivariate discriminant analysis and logistic regression for business failure prediction","volume":"38","author":"Li","year":"2011","journal-title":"Expert Systems with Applications"},{"key":"2026030906372871500_ref101","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.asoc.2014.01.018","article-title":"Statistics-based wrapper for feature selection: an implementation on financial distress identification with support vector machine","volume":"19","author":"Li","year":"2014","journal-title":"Applied Soft Computing"},{"issue":"4","key":"2026030906372871500_ref102","doi-asserted-by":"publisher","first-page":"1762","DOI":"10.1016\/j.eswa.2007.08.070","article-title":"A practical approach to credit scoring","volume":"35","author":"Min","year":"2008","journal-title":"Expert Systems with Applications"},{"issue":"5","key":"2026030906372871500_ref103","doi-asserted-by":"publisher","DOI":"10.1149\/1.1890701","article-title":"PEO-based polymer electrolytes with ionic liquids and their use in lithium metal-polymer electrolyte batteries","volume":"152","author":"Shin","year":"2005","journal-title":"Journal of The Electrochemical Society"},{"issue":"2","key":"2026030906372871500_ref104","doi-asserted-by":"publisher","first-page":"738","DOI":"10.1016\/j.ejor.2006.04.019","article-title":"Using Bayesian networks for bankruptcy prediction: some methodological issues","volume":"180","author":"Sun","year":"2007","journal-title":"European Journal of Operational Research"},{"issue":"7","key":"2026030906372871500_ref105","doi-asserted-by":"publisher","first-page":"926","DOI":"10.1287\/mnsc.38.7.926","article-title":"Managerial applications of neural networks: the case of bank failure predictions","volume":"38","author":"Tam","year":"1992","journal-title":"Management Science"},{"issue":"4","key":"2026030906372871500_ref106","first-page":"170","article-title":"A decision support system to predict financial distress. The case of Romania","volume":"18","author":"Tudor","year":"2015","journal-title":"Romanian Journal of Economic Forecasting"},{"key":"2026030906372871500_ref107","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1016\/j.knosys.2011.08.001","article-title":"The prediction for listed companies\u2019 financial distress by using multiple prediction methods with rough set and Dempster\u2013Shafer evidence theory","volume":"26","author":"Xiao","year":"2012","journal-title":"Knowledge-Based Systems"},{"key":"2026030906372871500_ref108","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.knosys.2014.03.007","article-title":"Financial ratio selection for business failure prediction using soft set theory","volume":"63","author":"Xu","year":"2014","journal-title":"Knowledge-Based Systems"}],"container-title":["Kybernetes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/K-09-2023-1888\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/k\/article-pdf\/54\/9\/4709\/10358610\/k-09-2023-1888en.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/www.emerald.com\/k\/article-pdf\/54\/9\/4709\/10358610\/k-09-2023-1888en.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T10:37:35Z","timestamp":1773052655000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.emerald.com\/k\/article\/54\/9\/4709\/1259621\/Default-prediction-modeling-DPM-with-machine"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,17]]},"references-count":111,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,10,14]]}},"URL":"https:\/\/doi.org\/10.1108\/k-09-2023-1888","relation":{},"ISSN":["0368-492X","1758-7883"],"issn-type":[{"value":"0368-492X","type":"print"},{"value":"1758-7883","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,17]]}}}