Metaheuristic Algorithms and Modern Credit Classification Methods: A Systematic Review

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dc.authorid105929en_US
dc.contributor.authorAlınbaş, Hazar
dc.date.accessioned2020-10-12T13:20:31Z
dc.date.available2020-10-12T13:20:31Z
dc.date.issued2020
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractNumber of proposed advanced analysis methods, which try to successfully predict if applicants are going to default in credit applications show an increasing pattern, especially after the Global Financial Crisis. Alternative to conventional statistical classification methods, machine learning methods arrive on the scene; they have capability to reveal information from the data independently from constraints and assumptions. Along with machine learning methods, metaheuristic algorithms that substantially improves classification performances take part in studies. Combined usages of learning methods and metaheuristic algorithms aim to benefit from the contemporary data storage and process capacities at the highest level and greatly contribute to credit risk assessment field. In this review study, credit classification studies that adopt metaheuristic algorithms in the analyses are examined with a systematic process, for the period after 2000. By forming a general framework, classification methods, metaheuristic algorithm implementations, algorithms' intended uses and performance assessment criteria are addressed. Examination showed that there is a growing interest, nevertheless method preferences are concentrated over a limited option. It is necessary to incorporate more novel metaheuristics and/or hybrid and combined usages to the studies. It is possible to say that progressive works parallel to the developments in computer and mathematical sciences will continuously contribute to the literature.en_US
dc.identifier.citationIstanbul Business Research, 49(1), 146-175en_US
dc.identifier.doi10.26650/ibr.2020.49.0033
dc.identifier.issn1434-6052
dc.identifier.scopusqualityQ1en_US
dc.identifier.trdizinid358087en_US
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/358087
dc.identifier.urihttps://doi.org/10.26650/ibr.2020.49.0033
dc.identifier.wosWOS:000561341800006en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.publisherİstanbul Üniversitesi Yayınevien_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.subjectCredit risken_US
dc.subjectCredit scoringen_US
dc.subjectCredit assessmenten_US
dc.subjectMachine learningen_US
dc.subjectMetaheuristics algorithmsen_US
dc.titleMetaheuristic Algorithms and Modern Credit Classification Methods: A Systematic Reviewen_US
dc.title.alternativeModern Kredi Sınıflandırma Çalışmaları ve Metasezgisel Algoritma Uygulamaları: Sistematik Bir Derlemeen_US
dc.typeArticleen_US

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