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

Haitham Nobanee, Hiba Shanti, Hind Aldhanhani, Abdulrahman Alblooshi and Essa Alali

Cogent Economics & Finance, 2022, vol. 10, issue 1, 2132638

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.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/23322039.2022.2132638 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:oaefxx:v:10:y:2022:i:1:p:2132638

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/OAEF20

DOI: 10.1080/23322039.2022.2132638

Access Statistics for this article

Cogent Economics & Finance is currently edited by Steve Cook, Caroline Elliott, David McMillan, Duncan Watson and Xibin Zhang

More articles in Cogent Economics & Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().