The rapid advancement of Large Language Models (LLMs) has introduced unprecedented opportunities for understanding customer intentions, emotions, financial awareness, and conversational context. Nevertheless, deploying LLMs in real-world financial systems remains challenging due to high computational costs, excessive token consumption, inference latency, limited explainability, and increasingly stringent regulatory requirements for transparent AI decision-making.
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