Big data and credit risk assessment: a bibliometric review, current streams, and directions for future research

dc.contributor.authorNobanee, Haitham
dc.contributor.authorShanti, Hiba
dc.contributor.authorAldhanhani, Hind
dc.contributor.authorETAL.
dc.date.accessioned2023-04-27T05:50:31Z
dc.date.accessioned2023-08-20T11:14:46Z
dc.date.available2023-04-27T05:50:31Z
dc.date.available2023-08-20T11:14:46Z
dc.date.issued2022-10
dc.description.abstractThis study aims to track the structural development of academic research on credit risk assessment and big data using bibliometric analysis. The bibliography is obtained from the Scopus database and contains all studies with citations published between 2012 and 2021. The study’s findings suggest that credit risk assessment and big data are vast fields that have increased significantly in the last nine years. Chinese researchers and organizations contributed the most to the documents. The current study concludes that several possibilities exist to improve the knowledge of credit risk assessment and big data. © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
dc.identifier.citationNobanee, H., Shanti, H., Aldhanhani, H., Alblooshi, A., & Alali, E. (2022). Big data and credit risk assessment: a bibliometric review, current streams, and directions for future research. Cogent Economics & Finance, 10(1), 2132638.
dc.identifier.doihttps://doi.org/10.1080/23322039.2022.2132638
dc.identifier.urihttps://edms.wexl.in/handle/1/4544
dc.subjectBibliometric
dc.subjectBig data
dc.subjectG32
dc.subjectNetwork mapping
dc.subjectRisk assessment
dc.titleBig data and credit risk assessment: a bibliometric review, current streams, and directions for future researchen_US
dc.typeArticleen_US

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