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| Format: | Recurso digital |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.19859470 |
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Table of Contents:
- <p>Conversational artificial intelligence (AI) provides a model shift from deterministic rule-based process automation to context-aware, always-on learning systems for financial operations. Toward that goal, this article presents a framework for escalation-aware conversational AI in financial operations, including a multi-dimensional signal architecture that leverages linguistic, behavioral, transactional, and relationship signals to make real-time, probabilistic escalation decisions for customers and service agents of financial institutions. Another key concept is the collaboration zone, where artificial intelligence and a human agent are processing in parallel, having distinct skills, and there is no explicit handoff of control between the agents. The curriculum builds on the human agents' reasoning to discover human-like reasoning paths and extend the AI competency frontier. It uses a high rate of automation while also ensuring highly satisfactory customer experiences similar to those of human agents. Other considerations include implementation architecture; the transformation of the workforce; QA and continuous improvement operations; as well as quests for proactive engagement, multimodal interaction, and federated learning; as well as the evolution of autonomous agents.</p>