LEARNER · GLOBAL
What is RAG? How banks use retrieval-augmented generation to ground AI answers in real data
RAG (Retrieval-Augmented Generation) is a technique where an AI model fetches relevant documents or data from a knowledge base before answering a question, rather than relying only on its training. For banks: a customer-service chatbot uses RAG to pull account details and policies, then generates an answer grounded in current, accurate information instead of hallucinating.
WHY IT MATTERS
RAG is critical for BFSI compliance; it reduces AI-generated false claims and makes AI outputs auditable. Without RAG, bank LLMs can invent loan terms or regulatory rules, creating legal liability.