Title: Comprehensive survey on modern technology for improved bank credit risk

Authors: Aishwarya Kumar; Ankita Srivastava; Puneet Kumar Gupta

Addresses: ICFAI Business School, The ICFAI University, Dehradun, India ' ICFAI Business School, The ICFAI University, Dehradun, India ' ICFAI Business School, The ICFAI University, Dehradun, India

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.

DOI: 10.1504/IJBIS.2024.142287

International Journal of Business Information Systems, 2024 Vol.47 No.2, pp.173 - 189

Received: 26 Sep 2020
Accepted: 20 May 2021
Published online: 17 Oct 2024 *

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