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What is RAG (Retrieval-Augmented Generation) and why banks are building it into LLMs

RAG is a technique that feeds a language model live, external data (e.g., current interest rates, account balances, regulatory filings) before generating a response. Unlike a vanilla LLM that relies only on training data, RAG ensures answers stay fresh and factual.

WHY IT MATTERS

Banks deploy RAG to ground AI chatbots in real-time compliance rules and product terms, reducing hallucination (false outputs) and regulatory risk.

Source: AITechHive Editorial · 2026-07-18

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What is RAG (Retrieval-Augmented Generation) and why banks are building it into LLMs — ath — AITechHive