Evaluating the Impact of Explainable AI on User Trust in Financial Decision-Support Systems
Ramya Mandava, Sai Srinivas Vellela, Shobana Gorintla, Lavanya Dalavai, Nallapu Malathi, Koya Haritha · 2025
Explainable Artificial Intelligence (XAI) when applied to financial decision-support systems (FDSS) creates transparent environments which help users improve their trust and develop better decision outcomes. The research examines the influence of XAI on finance user trust by evaluating its model interpretability alongside transparency and ethical compliance. The paper explains how three XAI mechanisms such as SHAP values, LIME, and counterfactual explanations help improve user confidence and interaction. Users demonstrate more satisfaction with trust in FDSS systems integrated with XAI compared to black-box AI systems and these systems produce improved financial decisions. Human-Oriented XAI design serves as a key financial success factor because it guarantees the achievement of ethical behavior and operational success as well as enhanced adoption rates.