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

Nobanee, Haitham ORCID: 0000-0003-4424-5600, Shanti, Hiba, Aldhanhani, Hind, Alblooshi, Abdulrahman and Alali, Essa (2022) Big data and credit risk assessment: a bibliometric review, current streams, and directions for future research. COGENT ECONOMICS & FINANCE, 10 (1). 2132638-.

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Official URL: http://dx.doi.org/10.1080/23322039.2022.2132638

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.

Item Type:	Article
Uncontrolled Keywords:	credit risk, network mapping, risk assessment, bibliometric, big data
Divisions:	Faculty of Humanities and Social Sciences > School of Histories, Languages and Cultures
Depositing User:	Symplectic Admin
Date Deposited:	14 Feb 2023 10:43
Last Modified:	15 Mar 2024 18:12
DOI:	10.1080/23322039.2022.2132638
Open Access URL:	https://doi.org/10.1080/23322039.2022.2132638
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3168399