LEARNER · GLOBAL
What is RAG? Retrieval-augmented generation explained for finance professionals
RAG (Retrieval-Augmented Generation) is a technique where an AI model queries a database or document store to fetch relevant facts before generating an answer. Instead of relying only on weights learned during training, RAG pulls fresh, verified data—critical for compliance and accuracy in finance.
WHY IT MATTERS
RAG is the primary production pattern for bank AI: it prevents hallucination, grounds LLM outputs in audit trails, and enables real-time regulatory data integration without retraining models.