The Impact of Explainable AI on Transparent Decision-Making in Financial Systems

Abstract

This paper examines the role of Explainable Artificial Intelligence (XAI) in enhancing transparent decision-making processes within financial systems. With financial institutions increasingly adopting AI for decision-making, concerns around the 'black box' nature of traditional AI models have grown. XAI offers a solution by providing interpretable insights into complex algorithms, enabling stakeholders to understand, trust, and validate AI-driven decisions. This research explores the impact of XAI on regulatory compliance, risk management, and customer trust. It also discusses the challenges and limitations of integrating XAI in financial settings, highlighting the balance between model complexity and interpretability. Through a comprehensive review of existing literature and case studies, the paper underscores the potential of XAI to foster transparency, accountability, and fairness in the financial sector, ultimately contributing to more ethical and efficient decision-making frameworks.