LEARNER · GLOBAL
Retrieval-Augmented Generation (RAG): how LLMs ground themselves in live data
RAG is a technique that lets LLMs fetch real-time information from external databases or documents before answering, reducing hallucinations. Banks use RAG to build Q&A agents over customer data, compliance docs, or market feeds without fine-tuning the model. Example: a customer service bot pulling account history to answer balance queries accurately.
WHY IT MATTERS
RAG is the production workhorse in BFSI AI: enables LLM-based chatbots, compliance assistants, and risk dashboards to stay current without expensive model retraining.
Source: AITechHive · 2026-07-03