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What is RAG? How banks use it to ground AI in real data

RAG (Retrieval-Augmented Generation) is a technique where an AI model fetches relevant documents or data *before* answering a question, grounding its response in current, factual sources rather than relying on training-data knowledge alone. In BFSI, this prevents LLMs from 'hallucinating' bogus account balances or regulatory guidance.

WHY IT MATTERS

Banks deploying RAG reduce legal and compliance risk by forcing AI to cite sources and stay tethered to real datasets—critical for customer service bots, risk analysis, and regulatory reporting.

Source: AITechHive Editorial · 2026-05-23

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What is RAG? How banks use it to ground AI in real data — ath