Risk assessment in financial services: Advancing transparency and trust through explainable AI models

Hossain, Iftekhar and Ahmad, Rajan and Amin, Md. Rahad and Sultana, Nasrin and Chowdhury, Sajib (2025) Risk assessment in financial services: Advancing transparency and trust through explainable AI models. International Journal of Science and Research Archive, 16 (1). pp. 1409-1419. ISSN 2582-8185

Abstract

This paper explores the integration of Explainable Artificial Intelligence (XAI) models in financial services to enhance transparency and foster trust in risk assessment processes. It investigates how XAI techniques can demystify complex AI-driven credit and fraud risk models, enabling stakeholders to better understand, validate, and trust automated decisions. By addressing the challenges of opacity and accountability inherent in AI systems, this study highlights the pivotal role of explainability in promoting ethical, fair, and reliable financial services. The findings underscore the potential of XAI to transform risk management by balancing predictive accuracy with interpretability, thereby advancing transparency and trust in the financial ecosystem.

Item Type: Article
Official URL: https://doi.org/10.30574/ijsra.2025.16.1.2150
Uncontrolled Keywords: Explainable AI; Financial Risk Assessment; Transparency in Finance; AI Model Interpretability; Credit Risk Modeling; Fraud Detection in Financial Services
Date Deposited: 01 Sep 2025 12:21
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URI: https://eprint.scholarsrepository.com/id/eprint/4631