Exploring Explainable AI (XAI)
K Hemachandran · 2025
Artificial intelligence (AI) has significantly improved productivity in financial decision-making, but it has also raised concerns about equity, accountability, and transparency. Financial institutions are increasingly relying on complex, opaque AI models for credit scoring, fraud detection, and investment decisions; yet, these models often lack interpretability, which draws regulatory attention. Explainable Artificial Intelligence (XAI) is a vital solution that makes AI-driven decisions more transparent and understandable for regulators, consumers, and financial professionals. This chapter examines how XAI could ensure regulatory compliance, reduce bias, enhance risk management, and increase algorithmic transparency. Despite its potential, XAI implementation is challenging, particularly when it comes to balancing model interpretability and prediction accuracy and managing various legal needs between nations. In addition to being a compliance measure, the chapter emphasises that XAI should be utilised as a strategic tool to advance moral AI governance and long-term financial viability.