 Comprehensive survey on modern technology for improved bank credit riskAishwarya Kumar, Ankita Srivastava and Puneet Kumar Gupta International Journal of Business Information Systems, 2024, vol. 47, issue 2, 173-189 Abstract: This paper gives a coordinated literature study on present-day technology innovations in bank credit risk to recommend a superior comprehension of the extant status of the application of artificial intelligence and machine learning models. An investigation is performed employing data in journals, articles, and certain thesis. The existing systematic literature review (SLR) is steered by research questions that incorporate the recognisable proof of advancements, data science algorithms, and the utilisation of high-tech models in evaluating credit risk in banks. The outcome identifies the forms and engagement of current financial technology in default risk. It intends to create taxonomy of financial technologies and amass information in the fields of credit underwriting, exposure estimation, text mining, blockchain, and the use of artificial intelligence in credit risk management. The paper will conclude with future research agendas and directions to transform the customary financial framework. Keywords: credit risk; banks; machine learning; credit models; artificial intelligence; systematic literature; modern technologies; fintech. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbisy:v:47:y:2024:i:2:p:173-189 Access Statistics for this article More articles in International Journal of Business Information Systems from Inderscience Enterprises Ltd |
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