CONSUMER CREDITS AND MACHINE LEARNING
dc.authorid | 0000-0001-9577-7274 | |
dc.authorscopusid | 58548283900 | |
dc.authorwosid | JTS-3767-2023 | |
dc.contributor.author | Aksu, Mervan | |
dc.date.accessioned | 2023-12-28T12:15:02Z | |
dc.date.available | 2023-12-28T12:15:02Z | |
dc.date.issued | 2023 | |
dc.department | MAÜ, Fakülteler, İktisadi ve İdari Bilimler Fakültesi, İşletme Bölümü | en_US |
dc.description.abstract | The fusion of consumer credit analysis with machine learning algorithms has revolutionized credit risk assessment, providing banks with more efficient and reliable methods for evaluating creditworthiness. By leveraging these advanced techniques, banks can enhance their risk management practices, reduce the ratio of non-performing loans, and ultimately contribute to their profitability and stability in the financial market. As machine learning continues to evolve, it is likely to play an increasingly critical role in the financial sector and beyond. | en_US |
dc.identifier.endpage | 34 | en_US |
dc.identifier.isbn | 9786256408639 | |
dc.identifier.startpage | 23 | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.12514/5322 | |
dc.identifier.volume | 16 | en_US |
dc.institutionauthor | Aksu, Mervan | |
dc.language.iso | en | en_US |
dc.publisher | Eğitim yayınevi | en_US |
dc.relation.ispartof | CONSUMER CREDITS AND MACHINE LEARNING | en_US |
dc.relation.publicationcategory | Kitap Bölümü - Uluslararası | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Consumer Credits | en_US |
dc.subject | Machine Learning | en_US |
dc.title | CONSUMER CREDITS AND MACHINE LEARNING | en_US |
dc.title.alternative | International Research in Social, Human and Administrative Sciences XVI | en_US |
dc.type | Book Part | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | ed33f371-c30a-48e0-8e32-e291d327e182 | |
relation.isAuthorOfPublication.latestForDiscovery | ed33f371-c30a-48e0-8e32-e291d327e182 |
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