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

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.