Big data and credit risk assessment: a bibliometric review, current streams, and directions for future research
| dc.contributor.author | Nobanee, Haitham | |
| dc.contributor.author | Shanti, Hiba | |
| dc.contributor.author | Aldhanhani, Hind | |
| dc.contributor.author | ETAL. | |
| dc.date.accessioned | 2023-04-27T05:50:31Z | |
| dc.date.accessioned | 2023-08-20T11:14:46Z | |
| dc.date.available | 2023-04-27T05:50:31Z | |
| dc.date.available | 2023-08-20T11:14:46Z | |
| dc.date.issued | 2022-10 | |
| dc.description.abstract | This 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.citation | Nobanee, 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.doi | https://doi.org/10.1080/23322039.2022.2132638 | |
| dc.identifier.uri | https://edms.wexl.in/handle/1/4544 | |
| dc.subject | Bibliometric | |
| dc.subject | Big data | |
| dc.subject | G32 | |
| dc.subject | Network mapping | |
| dc.subject | Risk assessment | |
| dc.title | Big data and credit risk assessment: a bibliometric review, current streams, and directions for future research | en_US |
| dc.type | Article | en_US |
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