LEARNER · GLOBAL
What are agent loops, and why they matter for financial AI
An agent loop is a cycle where an AI model thinks through a problem (e.g., "should we approve this loan?"), takes an action (calls a calculator or database), observes the result, and repeats until it reaches a confident answer. Unlike simple prompts, agents can break complex tasks into steps and refine along the way.
WHY IT MATTERS
Banks deploying AI for underwriting, fraud detection, and reconciliation increasingly rely on agent loops to ensure decisions are auditable: the AI can show its reasoning step-by-step, which regulators and compliance teams require.
Source: AITechHive Research · 2026-07-20