Persistent and Conversational Multi-Method Explainability for Trustworthy Financial AI

arXiv:2605.11687v1 Announce Type: new Abstract: Financial institutions increasingly require AI explanations that are persistent, cross-validated across methods, and conversationally accessible to human decision-makers. We present an architecture for human-centered explainable AI in financial sentiment analysis that combines three contributions. First, we treat XAI artifacts -- LIME feature attributions, occlusion-based word importance scores, and saliency heatmaps -- as persistent, searchable ob